- Email: [email protected]
Perspectives of automatic control
Control Engineering Practice 19 (2011) 1399–1407
Contents lists available at SciVerse ScienceDirect
Control Engineering Practice journal homepage: www.elsevier.com/locate/conengprac
Perspectives of automatic control Rolf Isermann Institute of Automatic Control and Mechatronics, Technische Universit¨ at Darmstadt, Landgraf-Georg-Str. 4, 64283 Darmstadt, Germany
a r t i c l e i n f o
abstract
Article history: Received 10 August 2011 Accepted 18 August 2011 Available online 4 October 2011
A short view is given on the role of automatic control with regard to technological developments in various process categories like manufacturing, power and process industries, transportation and vehicles, biological systems, and ecological/social systems. Some current developments in the components of automatic control systems are then considered, ranging from smart sensors and actuators, to bus-connected decentralized computer control hardware and control software with model-based control functions. Increasingly, computer-assisted modeling, identification methods and special development tools like hardware-in-the-loop simulation systems support the control function development. A further step is the integration of processes and their control such as the conjoining of mechanics and electronics to form mechatronics. Finally, some examples of the present roles of automation in modern technological and scientific developments are given, and some perspectives for the development in the near future are stated. Throughout the article a shell-oriented graphical representation is used to show the process categories considered, the subsystems and components and related examples of the technological and functional developments. The intention is to explain the role of automatic control, in particular to a general community, not necessarily expert in the field. & 2011 Elsevier Ltd. All rights reserved.
Keywords: Technological developments Process categories Control hardware Control software Role of automation Future perspectives
1. Introduction Automatic control engineering covers several technical and scientific disciplines including measurement techniques, actuation principles, information systems, micro and main frame computers and automatic control methods based on system theory. The reasons to apply automatic control include, for example replacement of human operators, the stabilization and damping of dynamic processes, precise control of technical and nontechnical processes, increasing a process or product performance, maintenance of safety and product quality, and providing human comfort. The automatic control functions are implemented at several levels, as continuous and sequential feedforward and continuous feedback control at the lowest level, controller adaptation, supervision and fault management at the medium level and plant optimization, scheduling and human machine operation in the highest level. Because humans are removed from direct manipulation of the processes, automatic control must function in a very reliable and safe manner. The design of suitable functions for continuous and sequential logic control follows basic general principles, as well as process-dependent tailored solutions, both of which stem from systems and control theoretical considerations.
E-mail address: [email protected] 0967-0661/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.conengprac.2011.08.004
In 2008 the worldwide turnover of electrical automation production was 306 Billion EUR, distributed graphically according to Fig. 1. The annual increase from 2006 to 2008 was around 8–9%. This means that the field of automation has developed to a remarkable share of technical systems with a strong growth and also is an important part of many modern processes and products.
2. Automatic control systems: the current role for advanced technologies Some decades ago control was mainly designed for lower level automation tasks like speed control of drives, position control of elevators, temperature and pressure control in power and chemical plants, heading and altitude control of aircraft, and sequence control of machine tools. Since then the control tasks have become more comprehensive and now are recognized as an important part of advanced technologies. Though there are many similarities the nature and implementation of control functions depend on the types of process, i.e. show process-dependent characteristics. Fig. 2 shows five process categories as arranged in the IFAC coordination committees. These groups of processes include different advanced technologies, all of which are essentially supported by automatic control. This is illustrated further in Fig. 3. Within manufacturing, for example, machine tool centers require sequential control for the different operating steps, along
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R. Isermann / Control Engineering Practice 19 (2011) 1399–1407
with high precision continuous control for speeds, position and forces. Industrial robots amount to about 5.5 Millions worldwide, with about 200–300 robots per 10 000 workers in technological leading countries. Mobile robots need extended control to cover navigation and supply chain management while the digital
Fig. 1. World production turnover of electrical automation. 2008: 306 Bill. EURO. Source: ZVEI, Frankfurt (2010) (The German electrical and electronics industry, based on national statistical data).
Fig. 2. Main process categories within IFAC according to its coordination committees.
factory concept includes higher level scheduling control. Major effort in the field of electrical power generation address the controlled extract of energy from regenerative sources in water, wind, geothermal and solar plants. This means that numerous and strongly fluctuating electrical supply units then feed wide electrical compound networks. Hence, decentralized control and overall optimal load dispatch is required. The demanded constant network frequency will with the strongly fluctuating, weatherdependent power from wind and solar units mainly be controlled by highly dynamic coal and water power plants. Savings in fossil fuel resources require good dynamical and control performance from steam boilers and their turbines. One important development step would be the availability of efficient energy storages, e.g. with more pump-water-storage plants, air pressure, thermal and electrical battery storage facilities, whose efficiency all depend strongly on control-oriented management. A further increase in the safety and reliability of coal and nuclear power plants demands many multi-variable control and supervision tasks, and improved fault tolerance of the hundreds of measurements and actuators found in a single plant. The chemical process industries, mineral and mining have to face shortages in raw materials and therefore more difficult exploration and production and increasing prices. In many cases the process efficiency needed and savings in energy can be reached by improved control performance, e.g. by moving set points closer to technological limits and achieving more constant product quality. The precise control of some nonlinear processes (e.g. reactors) in continuous or batch operating mode is still a challenge. For example, it is estimated that with increased use of speedcontrolled pumps for flow-rate control instead of throttling valves, about 5% of energy consumption can be saved. Cold rolling mills are an example where the geometrical precision of the strip thickness in the range of 5 mm directly depends on the control performance of the strongly coupled thickness and force control of tandem mills. Transportation and vehicles is another field where dynamics and automatic control play an important role. The first example is where internal combustion engines are the dominant form of propulsion. Fuel saving and very low emissions became only possible by the combination of, e.g. improved combustion,
Fig. 3. Some process-oriented developments which depend on automatic control.
R. Isermann / Control Engineering Practice 19 (2011) 1399–1407
different catalytic converters and particulate filters and their digital electronic control. The current state-of-the-art is characterized by high pressure common rail injection with piezoelectrical injectors, multiple injection pulses, turbo charging with variable geometry turbines, exhaust gas recirculation and complex nonlinear control with at least 6–12 main manipulated variables. Automobiles continue to be equipped with an increasing number of driver-assistance systems. This began with antilock braking (ABS) in 1978, electronic stability control (ESC) by individual wheel braking in 1995, and continued with adaptive cruise control (ACC) in 1999 and with stop-and-go in 2008. The introduction of the ESC, which simply stabilizes a spinning car by individual wheel braking, subsequently led to a 40% decrease in related serious accidents. Present day developments include, e.g. anti-collision avoidance systems by using RADAR or LIDAR and video cameras, as well as emergency braking and steering. These are all examples where nonlinear digital control, together with navigation and decision making for accident-avoidance strategies, saves the health and lives of passengers. A huge step forward has occurred in fault-tolerant fly-by-wire aircraft since 1987, invoking multiple redundancies in sensors, actuators and control computers. These rely totally on reliable and safe automatic control functions (Goupil, 2009). Beside the use of new light-weight glass and coal fiber materials, one of the present goals in aircraft design is the increase in electrical components (actuators, brakes) instead of hydraulic ones (allelectric aircraft). Fully autonomously flying unmanned-aircraftvehicles (UAV) are a further example of control systems with several higher automation levels to achieve navigation and mission-related tasks, including intelligent decision making. High speed trains or tilting trains and magnetic levitated (MAGLEV) trains in particular contain power-electronic-controlled electrical drives, controlled suspension systems and many supervision functions. Automated container transport at harbors in connection with ship loading and unloading is another field which has developed in recent years. Needless to say that space missions, from the launching rocket, through spacecraft or satellite control, re-entry and landing of space shuttles would be impossible without highly sophisticated multi-level, redundant control systems. Biosystems are another upcoming area with increasing control functions. Because of the shortage of food and limited agricultural areas automated agriculture, precision farming, growth optimization and optimized irrigation systems all need more automatic, distributed control. Furthermore, there are many examples within biomedical engineering, like implants, artificial organs, dialysismachines or power-assisted prothesis, where automatic control directly keeps the biomedical process within specified tolerances and supports the handicapped humans in their difficult life. Finally, ecological and social systems as nontechnical areas exhibit many control-related phenomena. Therefore, the study of the input/output behavior and the eigenbehavior of subsystems is essential for understanding the overall dynamics including stability. Myriads of feedback microsystems govern these huge systems and produce interesting observable drifts and cycles on a macrolevel. It is also fascinating how swarms of birds or fishes are organized and controlled (Anderson, 2006).
3. Automatic control components Automatic control systems usually consist of four subsystems (see Fig. 4):
Sensors and measurement systems. Actuator and drive systems.
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Fig. 4. Subsystems of automatic control.
Fig. 5. Components of automatic control systems.
Automation/control hardware. Automation/control software. These subsystems are further detailed in Fig. 5 by expanding the shell presentation. Conventional sensors, such as those for pressure, flow-rate, level, position, voltage and current have a mature and reliable status with standardized outputs. They have been enhanced by new measurement principles, for example, touchless measurement of position and motion, or inductive and piezo-electric effects for gas or liquid chemical concentrations. Increasingly the sensor components include data preprocessing electronics (ASICS or microprocessors), performing signal filtering, temperature and other compensation, Fourier- or wavelet-analysis for periodic signals and can produce the results in the form of a digital bus protocol (CAN, Profibus, Ethernet, etc.).
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Newer developments include wireless transmission of measurements, either battery driven or by energy harvesting from the environment (e.g. solar). Thus, distributed sensor networks are more easily possible (for oil exploration, irrigation systems, mining, and buildings) or additional sensors can easily be installed in existing plants without adding new cables. Standardized frequencies are 448, 868, 2402–2482 MHz. RFID (radio frequency identification) is on the way to replace barcodes (on transportation, manufacturing, and warehouse-automation). A further new field is sensor fusion, for example by generating an electronic image of a situation in front of a vehicle, by
integrating RADAR and video camera pictures. To support such applications modern sensors carry integrated microelectronics, resulting in smart sensors or sensor systems, compare Fig. 6. Conventional actuators use electrical, pneumatic or hydraulic auxiliary energy, see Fig. 7. All kinds of electrical drives, like universal, AC synchronous and asynchronous motors, DC motors with brushes or electronic communication or stepper motors are usually linked to a gear to generate the motion of a valve or a flap or to generate a force. Pneumatic valves are still used in chemical plants for safety reasons and hydraulic actuators dominate for generating large forces with relatively low weight. More recently,
Fig. 6. Some current developments in sensor technology.
Fig. 7. Some current developments in actuation technology.
R. Isermann / Control Engineering Practice 19 (2011) 1399–1407
actuation principles based on piezo-electrical effects are being used, for automotive fuel injection and electro-rheological or magneto-rheological effects, e.g. for semi-active shock absorbers. Advanced actuators carry integrated speed and/or position sensors and integrated microcomputers and, if required, power electronics, with direct connection to a communication bus. Special control algorithms can compensate for friction and faultmanagement facilities increasingly include fault detection and a forecast of the remaining lifetime. Special developments are observed for micromechanical actuators, with inductive or capacitive microdrives and high precision electromechanical actuators for manipulations in the nanometers range. Modern actuators are thus developing as smart components with integrated electronics. Automation/control hardware is based on microprocessors, microcontrollers, industrial PC (personal computer) cards or highly integrated microelectronics (e.g. ASICS, FPGA) for special high volume applications, Fig. 8. A large variety of devices from stand-alone controllers to flexible decentralized automation systems are available. Programmable logic controllers (PLC) for sequential control have, for several years, integrated digital continuous control. Industrial control systems are characterized by a decentralized multi-level architecture. The field level links sensors and actuators via field buses like Profibus, Profinet, CAN, Foundation Fieldbus to subsystem controllers, which are themselves connected by a subsystem bus like Ethernet, or TCP/IP (Intranet protocol). The top level then is a command level with PCs or mainframe computers where the overall automation is controlled by sending set points to the lower levels, see Fig. 8.
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The top level may also perform enterprise resource planning tasks. The overall result is an automation pyramid structure with a condensation of information and thus decreasing amounts of data from lower to higher levels. At the top level it can be observed that business process information systems and automation systems are coming together (Vogel-Heuser, Kegel, Bender, & Wucherer, 2009). The human–machine-interface (HMI) is an important part with a user-friendly and ergonomic design. Usually several human senses are triggered, like optical, acoustical, tactile and haptic. As well as push buttons, turning knobs, switches and keyboards, touch panels are increasingly used. Developments in microelectronics had a large influence on the design of the automation hardware. As the computing speed seems to have reached a limit for single processors, further progress is expected via parallel, dual and triple processors. The software of automation/control systems is mostly programmed, either in assembler for smaller units or in higher languages like C. The basic control functions are usually preconfigured with additional modules in the form of building blocks. Mostly, the control algorithms used are PID type ones. More sophisticated control methods usually require dynamic process models, which are obtained by theoretical/physical model building or by experiments with identification methods or a combination of both (semi-physical models). Many model-based control methods have been developed over the last five decades such as internal model control, state-space control with observers and stochastic control for linearizable processes or predictive
Fig. 8. Some present developments in automation/control hardware.
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Fig. 9. Some current developments in automation/control software.
control, bilinear control, sliding mode control, fuzzy control and neural net control for nonlinear processes. Adaptive control with parameter estimation or reference models adapt their parameters to changing process behavior or are simply used for self-tuning during commissioning. The software for a medium level of automation comprises supervision tasks, from fault diagnosis to fault management, to take care of availability and safety. Apart from conventional limit and trend checking, model-based fault-detection methods based on periodic or stochastic signal models and input/output process models have been developed over the last three decades. The fault-detection algorithms with process models are based on parity equations, observers or parameter estimation. At the higher levels extensive software systems are available for process optimization and scheduling. The validation and test of the software functions has become an extensive and laborious part of control system development. Special tools are applied, such as model-in-the-loop and hardware-in-the-loop systems. The latter combines real components like actuators or process components with real-time simulated process components using powerful computers. Software tools for the development of control systems include, for example, MATLAB/Simulink as well as domain specific packages (e.g. for electrical hydraulic or mechanical process). These are used for programming control methods and for simulation. Objectoriented model-building languages like Modelica or VHDL/AMS ease laborious model-building. Rapid control prototyping systems on high performance computers allow the development of control algorithms with high level languages, auto-coding and coupled
real processes (Hanselmann, 2008). The reuse of software has also received considerable attention. Fig. 9 illustrates some of these developments. Advanced automation systems exhibit an increased autonomy with decisions based on multi-sensor information, such as automatic landing of aircraft, self-navigation of unmanned vehicles (UAV) in the form of cars, aircraft, and ships and automotive anticollision avoidance systems. The design of automation systems for complicated and multivariable processes requires a systematic procedure from conception across several design stages to projection, implementation, testing and commissioning. The application of process models and simulation at an early stage leads not only to a more systematic design, but also to a faster implementation and commissioning with better control performance. For high volume products (like combustion engines, automobiles or hard disk drives) this also results in less prototypes.
4. Integration of processes and control Some technological developments show an integration of processes and control, as with ‘‘mechatronics’’, which means the integration of mechanics with electronics and information processing. This integration occurs between the components (hardware) and the information-driven functions (software). Such development involves finding an optimal balance between the basic mechanical structure, sensor and actuator implementation, automatic digital information processing and overall control. The
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Fig. 10. V-diagram for the development of mechatronic systems.
various integration steps can be seen in the V-type diagram of Fig. 10 (Isermann, 2005). Examples of mechatronic designed products include several automotive components, like fuel injection systems, ABS/ESC-brake systems, electrical power steering systems, and active suspension systems. Further examples are found in cameras, copying machines and hard-disk drives. Another example of component-oriented integration can be observed for ‘‘materials with sensors’’, which is sometimes called ‘‘adaptronics’’, where sensors built in materials measure stresses, temperatures, noise or turbulence in flows.
Automatic control supports a systematic structuring of the functions of technical, biological, economical and social processes.
Automatic control can be considered as providing the intelligence for modern products, processes and plants.
Automatic control connects different disciplines and is an integrator of different engineering fields.
Automatic control has developed into a fascinating field of practice and theory, and is an essential part of many innovative technologies and engineering education.
6. Citations 5. Current roles for automation/automatic control The examples discussed above of automatic control components, control methods and controlled processes have shown that this technological and scientific discipline is an important part of many modern processes and products. An essential aspect is that automatic control is based on general principles of system theory which supports interdisciplinary development and cross-fertilization. The current roles of automatic control can be summarized as:
Automatic control enables constant product quality, high
process efficiency, energy and new materials saving and environmental protection. Automatic control looks after the availability and safety of, e.g. industrial processes, vehicles and home appliances, amongst others. Automation in a broad sense reduces human effort, frees human workers from heavy work and from unfriendly environments and leads in general to a more comfortable life. It also enables 24 h production and is one reason for the reduced working hours of personnel. Many modern technologies depend on automatic control, indeed they are not realizable without automatic control.
A discussion of these general influences of automatic control ˚ ¨ on technology and society can also be found in Astr om (1994, 2006), Murray et al. (2002), Wellstead (2003) and IFAC milestone reports (Camacho, Basanez, & de la Puente, 2002; Chung & Misra, 2007; Horacek, Simandl, & Zitek, 2005). Some citations are: ‘‘Automatic control is one of the first systems disciplines to transcend the boundaries of traditional engineering fields’’ ˚ ¨ (Astr om, 1994). ‘‘Control is a true systems technology that has utility far beyond the conventional framework of linear feedback control’’ (Wellstead, 2003). ‘‘In many cases the innovation steps were made, if the control analyst acted as a scientific facilitator by linking the skills of team members via the common language of control systems’’ (Wellstead, 2003). ‘‘Dangerous work (Wucherer, 2008).
became
safer
through
automation’’
‘‘The control community must embrace new, information rich applications and generalize existing concepts to apply to
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systems at higher levels of decision making. The payoffs for investment in control research are systems that operate reliably, efficiently, and robustly,’’ AFOSR-Panel on future directions of control (Murray et al., 2002).
7. Future aspects of automation/automatic control Automatic control has, since a mechanical phase from ancient times on, an electrical and electronic phase from the 1930s to 1960s and a digital computer based phase from the 1960s/1970s now developed to a rather mature technical and scientific discipline. Future developments can be identified within the framework of general drivers of technical and economical developments. Some of these are known to be: Shortage of fossil energy and raw material resources: J Increasing energy and raw material prices. J Increased use of regenerative energy sources (wind, biofuel, solar), and storage. Shortage of food resources: J Population growth. J Basic food, clean water. Increased globalization of production and services: J Worldwide product development, manufacturing and distribution. J Seamless, real-time telecommunication. Increasing transportation and mobility: J More traffic (ground, air, sea). J Energy/time efficient mobility concepts. Increase of information technology: J E-commerce, E-development, E-conferences, etc. J Omnipresent information processing, large distributed networks. J Tele-presence: observation, services. Great importance of timely innovative products, manufacturing and materials J New materials, food processing. J Goods: smart devices, intelligent machines (hardware, software). J Know-how and innovation management, tools, experts: ‘‘human capital’’. Increasing importance of health support: J Increasing health awareness and lifetime. J Progress in medicine and bio-engineering. Based on already considered influences of automatic control on present technologies, it may be concluded that its role with regard to the general drivers listed above may even increase. Examples include more innovative products with integrated control because of shortages, more automated traffic, life-time optimization, highly interconnected world-wide production and economical systems and medical and biological control. It can be expected that, because of new measurement principles and more sensors, actuators and sophisticated control systems further improvements in efficiency, quality, availability, safety and environmental protection will be possible. The requirements of control systems will then become ever more complex and demanding.
8. Conclusions The foregoing discussion of perspectives for automatic control allows following statements to be made concerning the developments in the near future:
The development of automatic control is mainly driven by technology and challenging applications. The tightening of resources (energy, raw materials, food) require improved control of generation storage, distribution and consumption. Environmental protection demands minimization and control of pollution at the source. The integration of processes or products with digital control will further increase. Two kinds of integration can be identified: 1. Component oriented; integrates components and computers (mechatronics, adaptronics, biotronics). Requires simultaneous design of products/processes and control. 2. Advanced function oriented; integrates control and computation. Uses synergies between control theory, mathematics and computer science. Interdisciplinary engineering design will further increase, with automatic control serving as a system integrator. The use of computer supported design tools with interfaces between different disciplines will likewise expand. Automatic control methods will be extended to cover: J Complex, multi-dimensional systems: There is a need for structurally optimized, networked control. J Control of abnormal situations: Pre-hazardous, pre-accident situations require control with decision based structural changes. J Highly reliable and safe systems: These require fault management with fault-tolerant, reconfigurable systems. J Optimization of life cycles of processes and products: Asset-management systems will operate with condition monitoring, fault diagnosis and optimized maintenance. Further reading on future developments for automatic control can be found in IEEE Control Systems (1997), special issue (Anderson, 2006; ˚ om, ¨ Astr 2006; IEEE Control Systems, 1997; Isermann, 2009; Murray et al., 2002; Samad and Annaswamy, 2011; VDI/VDE-GMA, 2009; ZVEI, 2006). This contribution is based on a banquet speech at the IFAC World Congress in Seoul 2008 invited by former IFAC President Prof. Wook Kwon and was invited for publication in this journal by IFAC President Prof. Alberto Isidori.
References Anderson, B. D. O. (2006). Present developments in control theory. In IFAC 50th anniversary, Heidelberg, September 2006 /www.vdi.de/ifac50S. ˚ ¨ Astr om, K. H. (1994). The future of control. In Modelling, identification and control. (Norwegian research bulletin), Heidelberg, September 2006 /www.vdi.de/ ifac50S. ˚ ¨ Astr om, K. H. (2006). Present developments in control applications. In IFAC 50th anniversary, Heidelberg, September 2006 /www.vdi.de/ifac50S. Camacho, E. F., Basanez, L., & de la Puente, A. (2002). IFAC-Milestone Reports (6). Preprints, 15th IFAC-World congress, Barcelona, 21–26 July 2002. Chung, J. M., & Misra, P. (2007). IFAC-Milestone Reports (5). Preprints, 17th IFACWorld congress, Seoul. Goupil, P. (2009). AIRBUS state of the art and practices on fault detection and faulttolerant control. Plenary paper. Preprints 7th IFAC symposium SAFEPROCESS, 30th June–3rd July 2009, Barcelona, Spain. Hanselmann, H. (2008). Challenges in automotive software engineering. In 30th International conference on software engineering, Leipzig, Germany, 10–18 May 2008. Horacek, P., Simandl, M., & Zitek, P. (2005). IFAC-Milestone Reports (9). Preprints, 16th IFAC-World congress, programme, 3–8 July 2005. IEEE Control Systems (1997). Special issue on emerging technologies: Buildings, noise control, underwater vehicles, adaptive systems. IEEE-Control System, 17(6). Isermann, R. (2005). Mechatronic systems—fundamentals. London: Springer-Verlag. Isermann, R. (2009). Forward look—some thoughts on automatic control engineering. Proceedings of the IMechE. Vol. I: Journal of Systems and Control Engineering, 131–133. ˚ om, ¨ Murray, R. M., Astr K. H., Banda, S., Boyd, S., Brockett, R., Burns, J., et al. (2002). Future directions in control, dynamics and systems. Panel of AFOSR. /www.cds. caltech.edu/~murray/cdspanelS. /www.clubofrome.comS.
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Samad, T., & Annaswamy, A. M. (2011). The impact of control technology. IEEE Control Systems Society. /www.ieeecss.orgS. VDI/VDE-GMA (2009). Automatisierungstechnik 2020. /www.vdi.de/automation2020S. Vogel-Heuser, B., Kegel, G., Bender, K., & Wucherer (2009). Global information architecture for industrial automation. ATP—Automatisierungstechnische Praxis (pp. 108–115).
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Wellstead, P. E. (2003). Control and systems concepts in the innovation process. IEEE Control Magazine, December, 21–29. Wucherer, K. (2008). Interview. VDI-Nachrichten Nr. 26, 27th June 2008, p. 10. ZVEI (2006). Integrierte Technologie-Roadmap Automation 2015þ. Brochure ZVEI, Frankfurt. /www.zvei.orgS.
Contents lists available at SciVerse ScienceDirect
Control Engineering Practice journal homepage: www.elsevier.com/locate/conengprac
Perspectives of automatic control Rolf Isermann Institute of Automatic Control and Mechatronics, Technische Universit¨ at Darmstadt, Landgraf-Georg-Str. 4, 64283 Darmstadt, Germany
a r t i c l e i n f o
abstract
Article history: Received 10 August 2011 Accepted 18 August 2011 Available online 4 October 2011
A short view is given on the role of automatic control with regard to technological developments in various process categories like manufacturing, power and process industries, transportation and vehicles, biological systems, and ecological/social systems. Some current developments in the components of automatic control systems are then considered, ranging from smart sensors and actuators, to bus-connected decentralized computer control hardware and control software with model-based control functions. Increasingly, computer-assisted modeling, identification methods and special development tools like hardware-in-the-loop simulation systems support the control function development. A further step is the integration of processes and their control such as the conjoining of mechanics and electronics to form mechatronics. Finally, some examples of the present roles of automation in modern technological and scientific developments are given, and some perspectives for the development in the near future are stated. Throughout the article a shell-oriented graphical representation is used to show the process categories considered, the subsystems and components and related examples of the technological and functional developments. The intention is to explain the role of automatic control, in particular to a general community, not necessarily expert in the field. & 2011 Elsevier Ltd. All rights reserved.
Keywords: Technological developments Process categories Control hardware Control software Role of automation Future perspectives
1. Introduction Automatic control engineering covers several technical and scientific disciplines including measurement techniques, actuation principles, information systems, micro and main frame computers and automatic control methods based on system theory. The reasons to apply automatic control include, for example replacement of human operators, the stabilization and damping of dynamic processes, precise control of technical and nontechnical processes, increasing a process or product performance, maintenance of safety and product quality, and providing human comfort. The automatic control functions are implemented at several levels, as continuous and sequential feedforward and continuous feedback control at the lowest level, controller adaptation, supervision and fault management at the medium level and plant optimization, scheduling and human machine operation in the highest level. Because humans are removed from direct manipulation of the processes, automatic control must function in a very reliable and safe manner. The design of suitable functions for continuous and sequential logic control follows basic general principles, as well as process-dependent tailored solutions, both of which stem from systems and control theoretical considerations.
E-mail address: [email protected] 0967-0661/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.conengprac.2011.08.004
In 2008 the worldwide turnover of electrical automation production was 306 Billion EUR, distributed graphically according to Fig. 1. The annual increase from 2006 to 2008 was around 8–9%. This means that the field of automation has developed to a remarkable share of technical systems with a strong growth and also is an important part of many modern processes and products.
2. Automatic control systems: the current role for advanced technologies Some decades ago control was mainly designed for lower level automation tasks like speed control of drives, position control of elevators, temperature and pressure control in power and chemical plants, heading and altitude control of aircraft, and sequence control of machine tools. Since then the control tasks have become more comprehensive and now are recognized as an important part of advanced technologies. Though there are many similarities the nature and implementation of control functions depend on the types of process, i.e. show process-dependent characteristics. Fig. 2 shows five process categories as arranged in the IFAC coordination committees. These groups of processes include different advanced technologies, all of which are essentially supported by automatic control. This is illustrated further in Fig. 3. Within manufacturing, for example, machine tool centers require sequential control for the different operating steps, along
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R. Isermann / Control Engineering Practice 19 (2011) 1399–1407
with high precision continuous control for speeds, position and forces. Industrial robots amount to about 5.5 Millions worldwide, with about 200–300 robots per 10 000 workers in technological leading countries. Mobile robots need extended control to cover navigation and supply chain management while the digital
Fig. 1. World production turnover of electrical automation. 2008: 306 Bill. EURO. Source: ZVEI, Frankfurt (2010) (The German electrical and electronics industry, based on national statistical data).
Fig. 2. Main process categories within IFAC according to its coordination committees.
factory concept includes higher level scheduling control. Major effort in the field of electrical power generation address the controlled extract of energy from regenerative sources in water, wind, geothermal and solar plants. This means that numerous and strongly fluctuating electrical supply units then feed wide electrical compound networks. Hence, decentralized control and overall optimal load dispatch is required. The demanded constant network frequency will with the strongly fluctuating, weatherdependent power from wind and solar units mainly be controlled by highly dynamic coal and water power plants. Savings in fossil fuel resources require good dynamical and control performance from steam boilers and their turbines. One important development step would be the availability of efficient energy storages, e.g. with more pump-water-storage plants, air pressure, thermal and electrical battery storage facilities, whose efficiency all depend strongly on control-oriented management. A further increase in the safety and reliability of coal and nuclear power plants demands many multi-variable control and supervision tasks, and improved fault tolerance of the hundreds of measurements and actuators found in a single plant. The chemical process industries, mineral and mining have to face shortages in raw materials and therefore more difficult exploration and production and increasing prices. In many cases the process efficiency needed and savings in energy can be reached by improved control performance, e.g. by moving set points closer to technological limits and achieving more constant product quality. The precise control of some nonlinear processes (e.g. reactors) in continuous or batch operating mode is still a challenge. For example, it is estimated that with increased use of speedcontrolled pumps for flow-rate control instead of throttling valves, about 5% of energy consumption can be saved. Cold rolling mills are an example where the geometrical precision of the strip thickness in the range of 5 mm directly depends on the control performance of the strongly coupled thickness and force control of tandem mills. Transportation and vehicles is another field where dynamics and automatic control play an important role. The first example is where internal combustion engines are the dominant form of propulsion. Fuel saving and very low emissions became only possible by the combination of, e.g. improved combustion,
Fig. 3. Some process-oriented developments which depend on automatic control.
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different catalytic converters and particulate filters and their digital electronic control. The current state-of-the-art is characterized by high pressure common rail injection with piezoelectrical injectors, multiple injection pulses, turbo charging with variable geometry turbines, exhaust gas recirculation and complex nonlinear control with at least 6–12 main manipulated variables. Automobiles continue to be equipped with an increasing number of driver-assistance systems. This began with antilock braking (ABS) in 1978, electronic stability control (ESC) by individual wheel braking in 1995, and continued with adaptive cruise control (ACC) in 1999 and with stop-and-go in 2008. The introduction of the ESC, which simply stabilizes a spinning car by individual wheel braking, subsequently led to a 40% decrease in related serious accidents. Present day developments include, e.g. anti-collision avoidance systems by using RADAR or LIDAR and video cameras, as well as emergency braking and steering. These are all examples where nonlinear digital control, together with navigation and decision making for accident-avoidance strategies, saves the health and lives of passengers. A huge step forward has occurred in fault-tolerant fly-by-wire aircraft since 1987, invoking multiple redundancies in sensors, actuators and control computers. These rely totally on reliable and safe automatic control functions (Goupil, 2009). Beside the use of new light-weight glass and coal fiber materials, one of the present goals in aircraft design is the increase in electrical components (actuators, brakes) instead of hydraulic ones (allelectric aircraft). Fully autonomously flying unmanned-aircraftvehicles (UAV) are a further example of control systems with several higher automation levels to achieve navigation and mission-related tasks, including intelligent decision making. High speed trains or tilting trains and magnetic levitated (MAGLEV) trains in particular contain power-electronic-controlled electrical drives, controlled suspension systems and many supervision functions. Automated container transport at harbors in connection with ship loading and unloading is another field which has developed in recent years. Needless to say that space missions, from the launching rocket, through spacecraft or satellite control, re-entry and landing of space shuttles would be impossible without highly sophisticated multi-level, redundant control systems. Biosystems are another upcoming area with increasing control functions. Because of the shortage of food and limited agricultural areas automated agriculture, precision farming, growth optimization and optimized irrigation systems all need more automatic, distributed control. Furthermore, there are many examples within biomedical engineering, like implants, artificial organs, dialysismachines or power-assisted prothesis, where automatic control directly keeps the biomedical process within specified tolerances and supports the handicapped humans in their difficult life. Finally, ecological and social systems as nontechnical areas exhibit many control-related phenomena. Therefore, the study of the input/output behavior and the eigenbehavior of subsystems is essential for understanding the overall dynamics including stability. Myriads of feedback microsystems govern these huge systems and produce interesting observable drifts and cycles on a macrolevel. It is also fascinating how swarms of birds or fishes are organized and controlled (Anderson, 2006).
3. Automatic control components Automatic control systems usually consist of four subsystems (see Fig. 4):
Sensors and measurement systems. Actuator and drive systems.
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Fig. 4. Subsystems of automatic control.
Fig. 5. Components of automatic control systems.
Automation/control hardware. Automation/control software. These subsystems are further detailed in Fig. 5 by expanding the shell presentation. Conventional sensors, such as those for pressure, flow-rate, level, position, voltage and current have a mature and reliable status with standardized outputs. They have been enhanced by new measurement principles, for example, touchless measurement of position and motion, or inductive and piezo-electric effects for gas or liquid chemical concentrations. Increasingly the sensor components include data preprocessing electronics (ASICS or microprocessors), performing signal filtering, temperature and other compensation, Fourier- or wavelet-analysis for periodic signals and can produce the results in the form of a digital bus protocol (CAN, Profibus, Ethernet, etc.).
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Newer developments include wireless transmission of measurements, either battery driven or by energy harvesting from the environment (e.g. solar). Thus, distributed sensor networks are more easily possible (for oil exploration, irrigation systems, mining, and buildings) or additional sensors can easily be installed in existing plants without adding new cables. Standardized frequencies are 448, 868, 2402–2482 MHz. RFID (radio frequency identification) is on the way to replace barcodes (on transportation, manufacturing, and warehouse-automation). A further new field is sensor fusion, for example by generating an electronic image of a situation in front of a vehicle, by
integrating RADAR and video camera pictures. To support such applications modern sensors carry integrated microelectronics, resulting in smart sensors or sensor systems, compare Fig. 6. Conventional actuators use electrical, pneumatic or hydraulic auxiliary energy, see Fig. 7. All kinds of electrical drives, like universal, AC synchronous and asynchronous motors, DC motors with brushes or electronic communication or stepper motors are usually linked to a gear to generate the motion of a valve or a flap or to generate a force. Pneumatic valves are still used in chemical plants for safety reasons and hydraulic actuators dominate for generating large forces with relatively low weight. More recently,
Fig. 6. Some current developments in sensor technology.
Fig. 7. Some current developments in actuation technology.
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actuation principles based on piezo-electrical effects are being used, for automotive fuel injection and electro-rheological or magneto-rheological effects, e.g. for semi-active shock absorbers. Advanced actuators carry integrated speed and/or position sensors and integrated microcomputers and, if required, power electronics, with direct connection to a communication bus. Special control algorithms can compensate for friction and faultmanagement facilities increasingly include fault detection and a forecast of the remaining lifetime. Special developments are observed for micromechanical actuators, with inductive or capacitive microdrives and high precision electromechanical actuators for manipulations in the nanometers range. Modern actuators are thus developing as smart components with integrated electronics. Automation/control hardware is based on microprocessors, microcontrollers, industrial PC (personal computer) cards or highly integrated microelectronics (e.g. ASICS, FPGA) for special high volume applications, Fig. 8. A large variety of devices from stand-alone controllers to flexible decentralized automation systems are available. Programmable logic controllers (PLC) for sequential control have, for several years, integrated digital continuous control. Industrial control systems are characterized by a decentralized multi-level architecture. The field level links sensors and actuators via field buses like Profibus, Profinet, CAN, Foundation Fieldbus to subsystem controllers, which are themselves connected by a subsystem bus like Ethernet, or TCP/IP (Intranet protocol). The top level then is a command level with PCs or mainframe computers where the overall automation is controlled by sending set points to the lower levels, see Fig. 8.
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The top level may also perform enterprise resource planning tasks. The overall result is an automation pyramid structure with a condensation of information and thus decreasing amounts of data from lower to higher levels. At the top level it can be observed that business process information systems and automation systems are coming together (Vogel-Heuser, Kegel, Bender, & Wucherer, 2009). The human–machine-interface (HMI) is an important part with a user-friendly and ergonomic design. Usually several human senses are triggered, like optical, acoustical, tactile and haptic. As well as push buttons, turning knobs, switches and keyboards, touch panels are increasingly used. Developments in microelectronics had a large influence on the design of the automation hardware. As the computing speed seems to have reached a limit for single processors, further progress is expected via parallel, dual and triple processors. The software of automation/control systems is mostly programmed, either in assembler for smaller units or in higher languages like C. The basic control functions are usually preconfigured with additional modules in the form of building blocks. Mostly, the control algorithms used are PID type ones. More sophisticated control methods usually require dynamic process models, which are obtained by theoretical/physical model building or by experiments with identification methods or a combination of both (semi-physical models). Many model-based control methods have been developed over the last five decades such as internal model control, state-space control with observers and stochastic control for linearizable processes or predictive
Fig. 8. Some present developments in automation/control hardware.
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Fig. 9. Some current developments in automation/control software.
control, bilinear control, sliding mode control, fuzzy control and neural net control for nonlinear processes. Adaptive control with parameter estimation or reference models adapt their parameters to changing process behavior or are simply used for self-tuning during commissioning. The software for a medium level of automation comprises supervision tasks, from fault diagnosis to fault management, to take care of availability and safety. Apart from conventional limit and trend checking, model-based fault-detection methods based on periodic or stochastic signal models and input/output process models have been developed over the last three decades. The fault-detection algorithms with process models are based on parity equations, observers or parameter estimation. At the higher levels extensive software systems are available for process optimization and scheduling. The validation and test of the software functions has become an extensive and laborious part of control system development. Special tools are applied, such as model-in-the-loop and hardware-in-the-loop systems. The latter combines real components like actuators or process components with real-time simulated process components using powerful computers. Software tools for the development of control systems include, for example, MATLAB/Simulink as well as domain specific packages (e.g. for electrical hydraulic or mechanical process). These are used for programming control methods and for simulation. Objectoriented model-building languages like Modelica or VHDL/AMS ease laborious model-building. Rapid control prototyping systems on high performance computers allow the development of control algorithms with high level languages, auto-coding and coupled
real processes (Hanselmann, 2008). The reuse of software has also received considerable attention. Fig. 9 illustrates some of these developments. Advanced automation systems exhibit an increased autonomy with decisions based on multi-sensor information, such as automatic landing of aircraft, self-navigation of unmanned vehicles (UAV) in the form of cars, aircraft, and ships and automotive anticollision avoidance systems. The design of automation systems for complicated and multivariable processes requires a systematic procedure from conception across several design stages to projection, implementation, testing and commissioning. The application of process models and simulation at an early stage leads not only to a more systematic design, but also to a faster implementation and commissioning with better control performance. For high volume products (like combustion engines, automobiles or hard disk drives) this also results in less prototypes.
4. Integration of processes and control Some technological developments show an integration of processes and control, as with ‘‘mechatronics’’, which means the integration of mechanics with electronics and information processing. This integration occurs between the components (hardware) and the information-driven functions (software). Such development involves finding an optimal balance between the basic mechanical structure, sensor and actuator implementation, automatic digital information processing and overall control. The
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Fig. 10. V-diagram for the development of mechatronic systems.
various integration steps can be seen in the V-type diagram of Fig. 10 (Isermann, 2005). Examples of mechatronic designed products include several automotive components, like fuel injection systems, ABS/ESC-brake systems, electrical power steering systems, and active suspension systems. Further examples are found in cameras, copying machines and hard-disk drives. Another example of component-oriented integration can be observed for ‘‘materials with sensors’’, which is sometimes called ‘‘adaptronics’’, where sensors built in materials measure stresses, temperatures, noise or turbulence in flows.
Automatic control supports a systematic structuring of the functions of technical, biological, economical and social processes.
Automatic control can be considered as providing the intelligence for modern products, processes and plants.
Automatic control connects different disciplines and is an integrator of different engineering fields.
Automatic control has developed into a fascinating field of practice and theory, and is an essential part of many innovative technologies and engineering education.
6. Citations 5. Current roles for automation/automatic control The examples discussed above of automatic control components, control methods and controlled processes have shown that this technological and scientific discipline is an important part of many modern processes and products. An essential aspect is that automatic control is based on general principles of system theory which supports interdisciplinary development and cross-fertilization. The current roles of automatic control can be summarized as:
Automatic control enables constant product quality, high
process efficiency, energy and new materials saving and environmental protection. Automatic control looks after the availability and safety of, e.g. industrial processes, vehicles and home appliances, amongst others. Automation in a broad sense reduces human effort, frees human workers from heavy work and from unfriendly environments and leads in general to a more comfortable life. It also enables 24 h production and is one reason for the reduced working hours of personnel. Many modern technologies depend on automatic control, indeed they are not realizable without automatic control.
A discussion of these general influences of automatic control ˚ ¨ on technology and society can also be found in Astr om (1994, 2006), Murray et al. (2002), Wellstead (2003) and IFAC milestone reports (Camacho, Basanez, & de la Puente, 2002; Chung & Misra, 2007; Horacek, Simandl, & Zitek, 2005). Some citations are: ‘‘Automatic control is one of the first systems disciplines to transcend the boundaries of traditional engineering fields’’ ˚ ¨ (Astr om, 1994). ‘‘Control is a true systems technology that has utility far beyond the conventional framework of linear feedback control’’ (Wellstead, 2003). ‘‘In many cases the innovation steps were made, if the control analyst acted as a scientific facilitator by linking the skills of team members via the common language of control systems’’ (Wellstead, 2003). ‘‘Dangerous work (Wucherer, 2008).
became
safer
through
automation’’
‘‘The control community must embrace new, information rich applications and generalize existing concepts to apply to
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systems at higher levels of decision making. The payoffs for investment in control research are systems that operate reliably, efficiently, and robustly,’’ AFOSR-Panel on future directions of control (Murray et al., 2002).
7. Future aspects of automation/automatic control Automatic control has, since a mechanical phase from ancient times on, an electrical and electronic phase from the 1930s to 1960s and a digital computer based phase from the 1960s/1970s now developed to a rather mature technical and scientific discipline. Future developments can be identified within the framework of general drivers of technical and economical developments. Some of these are known to be: Shortage of fossil energy and raw material resources: J Increasing energy and raw material prices. J Increased use of regenerative energy sources (wind, biofuel, solar), and storage. Shortage of food resources: J Population growth. J Basic food, clean water. Increased globalization of production and services: J Worldwide product development, manufacturing and distribution. J Seamless, real-time telecommunication. Increasing transportation and mobility: J More traffic (ground, air, sea). J Energy/time efficient mobility concepts. Increase of information technology: J E-commerce, E-development, E-conferences, etc. J Omnipresent information processing, large distributed networks. J Tele-presence: observation, services. Great importance of timely innovative products, manufacturing and materials J New materials, food processing. J Goods: smart devices, intelligent machines (hardware, software). J Know-how and innovation management, tools, experts: ‘‘human capital’’. Increasing importance of health support: J Increasing health awareness and lifetime. J Progress in medicine and bio-engineering. Based on already considered influences of automatic control on present technologies, it may be concluded that its role with regard to the general drivers listed above may even increase. Examples include more innovative products with integrated control because of shortages, more automated traffic, life-time optimization, highly interconnected world-wide production and economical systems and medical and biological control. It can be expected that, because of new measurement principles and more sensors, actuators and sophisticated control systems further improvements in efficiency, quality, availability, safety and environmental protection will be possible. The requirements of control systems will then become ever more complex and demanding.
8. Conclusions The foregoing discussion of perspectives for automatic control allows following statements to be made concerning the developments in the near future:
The development of automatic control is mainly driven by technology and challenging applications. The tightening of resources (energy, raw materials, food) require improved control of generation storage, distribution and consumption. Environmental protection demands minimization and control of pollution at the source. The integration of processes or products with digital control will further increase. Two kinds of integration can be identified: 1. Component oriented; integrates components and computers (mechatronics, adaptronics, biotronics). Requires simultaneous design of products/processes and control. 2. Advanced function oriented; integrates control and computation. Uses synergies between control theory, mathematics and computer science. Interdisciplinary engineering design will further increase, with automatic control serving as a system integrator. The use of computer supported design tools with interfaces between different disciplines will likewise expand. Automatic control methods will be extended to cover: J Complex, multi-dimensional systems: There is a need for structurally optimized, networked control. J Control of abnormal situations: Pre-hazardous, pre-accident situations require control with decision based structural changes. J Highly reliable and safe systems: These require fault management with fault-tolerant, reconfigurable systems. J Optimization of life cycles of processes and products: Asset-management systems will operate with condition monitoring, fault diagnosis and optimized maintenance. Further reading on future developments for automatic control can be found in IEEE Control Systems (1997), special issue (Anderson, 2006; ˚ om, ¨ Astr 2006; IEEE Control Systems, 1997; Isermann, 2009; Murray et al., 2002; Samad and Annaswamy, 2011; VDI/VDE-GMA, 2009; ZVEI, 2006). This contribution is based on a banquet speech at the IFAC World Congress in Seoul 2008 invited by former IFAC President Prof. Wook Kwon and was invited for publication in this journal by IFAC President Prof. Alberto Isidori.
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