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Analog Computations and Current Problems of Automatic Control
Proceedings of the 13th IFAC Symposium on Information Control Problems in Manufacturing Moscow, Russia, June 3-5, 2009
Analog Computations and Current Problems of Automatic Control Robert R. Babayan Institute of Control Sciences of the RAS Profsoyuznaya 65, 117997 Moscow, Russia (+7-495-334-9301; e-mail: [email protected]) Abstract. The widespread use of analog computation in the past is no longer the case. It implies not only shutting down one of the sectors consuming analog microcircuits. In fact, it leads to narrowing the “knowledge base” on automatic control with a subsequent bias in training of the specialists. The way out can be found in wider application of analog computing subsystems, for instance, in testing predictive algorithms for moving objects control and by analysis of chaotic systems. There is hardware available and research to support such developments. systems to equations in the form of operator transfer functions and further on to analog model.
1. STATE OF THE ART Comprehensive modeling of the dynamics and synthesis of the algorithms and systems for control of complex objects today is done through the use of digital computers with the relevant software packages such as MATHLAB-SIMULINK and the appropriate methods. This is one of the many reasons why the modeling complexes using analog and analog-digital (hybrid) computations have almost completely run out of use now. The methods and systems for analog signal processing still have a prominent role to play only in the front-end of the modern systems for data collection and processing. A limited set of analog operations used there, such as scaling, filtering, sampling, storage, multiplexing etc., however, can be only viewed as preliminary signal processing for subsequent digital processing. However, the world view aspect of the analog methods and approaches remains important as one of the fundamental ways of representing properties of real object as data. For instance, Butkovsky (2003) explains that a basic analog element which is an operating amplifier with strong negative feedback, exemplifies “the control paradigm of the world”, i.e. rather a general principle of systems’ control. The computer capacity based on discrete arithmetic is close to be exhausted, and prototypes are already available of computers based not on binary but rather vector operations. Obviously future users will need to be open-minded with regard to problem solution techniques, algorithms and element base used in systems’ design. Consequently analog methods and approaches as well as fundamentals of the analog system engineering inevitably constitute an important part of the analytical apparatus of a modern control system designer. Indeed, analog representation is closely associated with many things, such as: frequency and phase-based methods of system analysis, stability criteria and quality indicators for systems with feedback, classification and structural diagrams of controllers etc. One has to mention here also the simple and obvious transition from a structural description of control 978-3-902661-43-2/09/$20.00 © 2009 IFAC
Developed countries produce enormous amounts of microchip-based operational amplifiers (over 0,6 billion a year) and many other analog computing elements – multipliers-divisors, functional modules, reference-voltage sources, analog switches, multiplexers and other. The progress in technology leads to further improvement of the parameters, such as drift of operational amplifiers, input currents, noise, or cut-off frequencies. Precision resistors and low-loss film capacitors become more and more available and affordable. Given the today’s level of development and scale of the analog element base, an analog computer of the state of the art precision and speed can be assembled using only mass produced items without any additional research and development. Obviously, installation of such an overwhelming amount of analog components requires a lot of specialists well versed in analog circuit engineering and relevant procedures as well as tools for their training. That’s why some companies still produce analog computers for training purposes. The above can be supplemented with some considerations of applied relevance. The designing of analog controllers of various applications most likely will continue in the near future. Many sensors including the ones installed in moving objects will remain analog as will the systems for primary processing of their signals, etc. It has to be mentioned that when the solution of most originally “analog” problems was rightfully referred to digital computers, there were some among them whose solution by analog methods would have been more direct and efficient. Since system research and design processes become more and more formalized, they are frequently implemented in a purely computer format with less attention to the underlying physics and the real context. Research skills with regard to preliminary, sometimes almost intuitive assessment of how adequate the model is, get gradually lost. Along with the above world view bias towards discrete methods and sequential algorithms this may result in the degradation of the present knowledge in the
1887
10.3182/20090603-3-RU-2001.0529
13th IFAC INCOM (INCOM'09) Moscow, Russia, June 3-5, 2009
field of control sciences and a bias in training of the specialists (Epshtein, 2003).
inertia-free response of the derivative of the predicted coordinate to control.
But such a common form of information communication as the interaction of a human operator with computer and its peripherals, although differing essentially from an interaction with, for instance, in-line simulator, even not necessarily analog, still is undoubtedly not subject to changes. Moreover, a number of technology sectors related to the one we are discussing here have originally been shaped as digitaloriented and respectively have acquired substantial methodology, hardware and software support. These include digital signal processing (DSP), digital filtering, digital transmission and data processing and other. There is no point in trying to implement analog approaches in these fields.
In such applications particularly useful is the potential high speed of analog devices achieved by parallel computation so that the solution of a complex equation or a system of differential equations of motion is done in one computing cycle and can be repeated dozens of thousands times a second. This enables implementing various versions of prediction not only in control of inertial objects but also in training the operators using simulators and mock-ups. The analog methods may also prove useful in reconstructing nonlinear dynamic systems with non-periodic oscillations (Pavlov et al., 1999). Such reconstruction needs determining in real time of the form and dimensionality of the system using the time curve of one of its coordinates. This and preceding examples both illustrate the use of analog devices in simulation, their main application has always been not obtaining numerical values but generation of processes, curves etc.
2. FUTURE Based on the above it stands to reason to reconsider the role of analog approaches and methods, specifically in the field of education. The focus, no doubt, should be on the applications where analog methods hold much promise based on: 1) Experience gained in the field of analog computations, their techniques and methods applied to solution of various problems 2) Some features of modern analog devices are in demand today (parallel computations, efficiency, noise-proof features). 3) Practically full coverage with the microelectronic devices which are constantly improved to meet the demand in many other sectors of technology. Useful properties of analog computers may be revealed to the greatest extent when used jointly with digital devices for inline simulation for testing onboard control systems i.e. where interaction is needed with real hardware and problems of dynamics are to be solved promptly. Specific noise-proof features of analog devices in the context of exposure to radiation may also prove to be useful, although we do not know of any representative statistics to prove it. For survival of moving objects not stable without control system it could be useful to duplicate the digital control system with a simplified analog subsystem including, among other things, some elements of prediction.
In summary, the fruitful field of application for analog computations seems to be the testing and implementation of control algorithms based on iterative solution of systems of ordinary differential equations, both linear and nonlinear. Obviously, the algorithms tested thereby should be incorporated into the digital control system. REFERENCES Butkovsky A.G. (2003) On a unified geometric theory of control, Problems of control, 1. Epshtein V.K. (2003) Anthropocentric information interaction (problems of terminology), Problems of control, 1. pp. 28-32. Gul’ko F.B., Novosel’tseva Zh.A. (1980) Application of methods of forecasting to synthesis of computerized control systems (СCS), Abstracts of presentations at VIII National Conference on Control, vol. 1, Tallinn. Pavlov A.N., Yanson N.B., Anishchenko V.S. (1999) Reconstruction of dynamic systems, Radiotechnology and electronics, 44 (9), pp. 1975-1092.
In general, the prediction of behavior of a dynamic object is reduced to implementation of a certain algorithm which enables determining future coordinates at arbitrary time t > t0 depending on its status at an initial time t0 in a point of space х0. Of a particular importance is prediction for a vast subclass of mechanical dynamic systems controlled with participation of human operator (flight vehicles, ships, submarines etc.). For a strict statement of the problem of prediction with regard to the controlled object with restrictions on the coordinates see Gul’ko and Novosel’tseva (1980). An important property of predictive systems in the sense of Gul’ko and Novosel’tseva (1980) is achieved by an accelerated model
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Analog Computations and Current Problems of Automatic Control Robert R. Babayan Institute of Control Sciences of the RAS Profsoyuznaya 65, 117997 Moscow, Russia (+7-495-334-9301; e-mail: [email protected]) Abstract. The widespread use of analog computation in the past is no longer the case. It implies not only shutting down one of the sectors consuming analog microcircuits. In fact, it leads to narrowing the “knowledge base” on automatic control with a subsequent bias in training of the specialists. The way out can be found in wider application of analog computing subsystems, for instance, in testing predictive algorithms for moving objects control and by analysis of chaotic systems. There is hardware available and research to support such developments. systems to equations in the form of operator transfer functions and further on to analog model.
1. STATE OF THE ART Comprehensive modeling of the dynamics and synthesis of the algorithms and systems for control of complex objects today is done through the use of digital computers with the relevant software packages such as MATHLAB-SIMULINK and the appropriate methods. This is one of the many reasons why the modeling complexes using analog and analog-digital (hybrid) computations have almost completely run out of use now. The methods and systems for analog signal processing still have a prominent role to play only in the front-end of the modern systems for data collection and processing. A limited set of analog operations used there, such as scaling, filtering, sampling, storage, multiplexing etc., however, can be only viewed as preliminary signal processing for subsequent digital processing. However, the world view aspect of the analog methods and approaches remains important as one of the fundamental ways of representing properties of real object as data. For instance, Butkovsky (2003) explains that a basic analog element which is an operating amplifier with strong negative feedback, exemplifies “the control paradigm of the world”, i.e. rather a general principle of systems’ control. The computer capacity based on discrete arithmetic is close to be exhausted, and prototypes are already available of computers based not on binary but rather vector operations. Obviously future users will need to be open-minded with regard to problem solution techniques, algorithms and element base used in systems’ design. Consequently analog methods and approaches as well as fundamentals of the analog system engineering inevitably constitute an important part of the analytical apparatus of a modern control system designer. Indeed, analog representation is closely associated with many things, such as: frequency and phase-based methods of system analysis, stability criteria and quality indicators for systems with feedback, classification and structural diagrams of controllers etc. One has to mention here also the simple and obvious transition from a structural description of control 978-3-902661-43-2/09/$20.00 © 2009 IFAC
Developed countries produce enormous amounts of microchip-based operational amplifiers (over 0,6 billion a year) and many other analog computing elements – multipliers-divisors, functional modules, reference-voltage sources, analog switches, multiplexers and other. The progress in technology leads to further improvement of the parameters, such as drift of operational amplifiers, input currents, noise, or cut-off frequencies. Precision resistors and low-loss film capacitors become more and more available and affordable. Given the today’s level of development and scale of the analog element base, an analog computer of the state of the art precision and speed can be assembled using only mass produced items without any additional research and development. Obviously, installation of such an overwhelming amount of analog components requires a lot of specialists well versed in analog circuit engineering and relevant procedures as well as tools for their training. That’s why some companies still produce analog computers for training purposes. The above can be supplemented with some considerations of applied relevance. The designing of analog controllers of various applications most likely will continue in the near future. Many sensors including the ones installed in moving objects will remain analog as will the systems for primary processing of their signals, etc. It has to be mentioned that when the solution of most originally “analog” problems was rightfully referred to digital computers, there were some among them whose solution by analog methods would have been more direct and efficient. Since system research and design processes become more and more formalized, they are frequently implemented in a purely computer format with less attention to the underlying physics and the real context. Research skills with regard to preliminary, sometimes almost intuitive assessment of how adequate the model is, get gradually lost. Along with the above world view bias towards discrete methods and sequential algorithms this may result in the degradation of the present knowledge in the
1887
10.3182/20090603-3-RU-2001.0529
13th IFAC INCOM (INCOM'09) Moscow, Russia, June 3-5, 2009
field of control sciences and a bias in training of the specialists (Epshtein, 2003).
inertia-free response of the derivative of the predicted coordinate to control.
But such a common form of information communication as the interaction of a human operator with computer and its peripherals, although differing essentially from an interaction with, for instance, in-line simulator, even not necessarily analog, still is undoubtedly not subject to changes. Moreover, a number of technology sectors related to the one we are discussing here have originally been shaped as digitaloriented and respectively have acquired substantial methodology, hardware and software support. These include digital signal processing (DSP), digital filtering, digital transmission and data processing and other. There is no point in trying to implement analog approaches in these fields.
In such applications particularly useful is the potential high speed of analog devices achieved by parallel computation so that the solution of a complex equation or a system of differential equations of motion is done in one computing cycle and can be repeated dozens of thousands times a second. This enables implementing various versions of prediction not only in control of inertial objects but also in training the operators using simulators and mock-ups. The analog methods may also prove useful in reconstructing nonlinear dynamic systems with non-periodic oscillations (Pavlov et al., 1999). Such reconstruction needs determining in real time of the form and dimensionality of the system using the time curve of one of its coordinates. This and preceding examples both illustrate the use of analog devices in simulation, their main application has always been not obtaining numerical values but generation of processes, curves etc.
2. FUTURE Based on the above it stands to reason to reconsider the role of analog approaches and methods, specifically in the field of education. The focus, no doubt, should be on the applications where analog methods hold much promise based on: 1) Experience gained in the field of analog computations, their techniques and methods applied to solution of various problems 2) Some features of modern analog devices are in demand today (parallel computations, efficiency, noise-proof features). 3) Practically full coverage with the microelectronic devices which are constantly improved to meet the demand in many other sectors of technology. Useful properties of analog computers may be revealed to the greatest extent when used jointly with digital devices for inline simulation for testing onboard control systems i.e. where interaction is needed with real hardware and problems of dynamics are to be solved promptly. Specific noise-proof features of analog devices in the context of exposure to radiation may also prove to be useful, although we do not know of any representative statistics to prove it. For survival of moving objects not stable without control system it could be useful to duplicate the digital control system with a simplified analog subsystem including, among other things, some elements of prediction.
In summary, the fruitful field of application for analog computations seems to be the testing and implementation of control algorithms based on iterative solution of systems of ordinary differential equations, both linear and nonlinear. Obviously, the algorithms tested thereby should be incorporated into the digital control system. REFERENCES Butkovsky A.G. (2003) On a unified geometric theory of control, Problems of control, 1. Epshtein V.K. (2003) Anthropocentric information interaction (problems of terminology), Problems of control, 1. pp. 28-32. Gul’ko F.B., Novosel’tseva Zh.A. (1980) Application of methods of forecasting to synthesis of computerized control systems (СCS), Abstracts of presentations at VIII National Conference on Control, vol. 1, Tallinn. Pavlov A.N., Yanson N.B., Anishchenko V.S. (1999) Reconstruction of dynamic systems, Radiotechnology and electronics, 44 (9), pp. 1975-1092.
In general, the prediction of behavior of a dynamic object is reduced to implementation of a certain algorithm which enables determining future coordinates at arbitrary time t > t0 depending on its status at an initial time t0 in a point of space х0. Of a particular importance is prediction for a vast subclass of mechanical dynamic systems controlled with participation of human operator (flight vehicles, ships, submarines etc.). For a strict statement of the problem of prediction with regard to the controlled object with restrictions on the coordinates see Gul’ko and Novosel’tseva (1980). An important property of predictive systems in the sense of Gul’ko and Novosel’tseva (1980) is achieved by an accelerated model
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