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Integrated Simulation System for Design and Evaluation of Distributed Computer Control Systems
© IF,-\(: !llh T riellnial World Congress llll(b\H_'SI, HUllgan-, 19K-4
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INTEGRA TED SIMULATION SYSTEM FOR DESIGN AND EVALUATION OF DISTRIBUTED COMPUTER CONTROL SYSTEMS H. Kasahara and S. Narita De/mrtme1l1 of Electrical Engi1U'ering. l\'asl'da L'nil 1f'rsily. Tokyu 160. Japan
Abstract. This paper presents an integrated simulation system to be used for the design and evaluation of distributed computer control systems. The simulation system is comprised of Communication Performance Evaluation Module, System Reliability Evaluation Module and Control Performance Evaluation Module. Different from conventional all-software approaches, dedicated hardware facilities such as a parallel multimicroprocessor system for real-time simulation of controlled system dynamics and a mimic communication system are used advantageously to achieve best overall economy of simulation in conjunction with software simulation modules. The features of the proposed of simulation system as applied to several dfstributed computer control systems with different system architectures are described. Keywords. Computer control; Markov processes; Network analysers; Parallel processing; Reliability thory; Local area network; Simulation; Distributed computer control systems.
OVERVIEW OF INTEGRATED SIMULATION SYSTEM
COMMUNICATION PERFORMANCE EVALUATION MODULE
This paper presents an integrated simulation system to be used for the design and analysis stages of Distributed Computer Control Systems (DCCS). A variety of evaluation criteria are involved and must be duly taken into account to implement DCCS, which typically is made up of multiple computers or nodes interconnected by some communication net. Among other evaluation criteria, communication performance, system reliability and control performance may be considered the triumvirate. The present simulation system is aimed at the integrated evaluation of the aforementioned criteria and comprised of the following modules .
The Communication Performance Evaluation Module (CMPEM) is a simulation module to be used for the evaluation of communication performance of DCCS. It is broken down into the following submodules. (a)
(b)
5.5.5:
All-software simulation submodule written in GPSS (General- Purpose Simulation System) . H.S.S: Hybrid hardware-software simulation submodule.
The former simulation submodule is suited for rough or detailed evaluation of a wide variety of communication systems with possibly different configurations, dimensions, transmission rates and communication protocols. In this sense, it is provided with more flexibility than the latter submodule, which may be used to advantage for more cost-effective evaluation of specific communication nets. Emphasis is placed on the evaluation of the communication performance of local area networks (LAN) such as IEEE Project 802 (Harrison, 1982) as they are used in real-time control environments because few contributions have so far been reported to the potential capabilities of LAN in industrial environments (factory 3utomation, for example).
(1) Communication Performance Evaluation Module(CMPEM). (2) System Reliability Evaluation Module (SREM) . (3) Control Performance Evaluation Module(CNPEM). here stands for A module as defined either an all-software simulation package or a combination of specific software and dedicated hardware to perform jointly a specific simulation function. Different from all-software evaluation systems or hardware-oriented testbeds of DCCS, use is made of the hybrid (joint hardware-software) approach to take advantage of the inherent features of hardware and software . In what follows, the function, configuration and features of each of the above-mentioned modules are described in detail.
The authors would like to add that they purposely avoided the use of the queuetheoretic approach except for the validation check of the simulation results since the formulae derived on the basis of queuing theory only apply to a few idealized cases, e.g., simplified communication protocols, uniform message 2669
H. Kasahara and S. Narita
2670
generation and destination distributions. Functional Requirements and Criteria of Industrial LAN
Evaluation
When a local area network is to be applied to industrial real-time control, the following functions must be duly taken into consideration: (a) Responsiveness (real-time capabilities) (b) Fairness (n-to-n communication) (c) High data transmission rate (d) Expandability (e) High reliability and maintainability variety of LAN Among a wide configurations such as bus, ring, and and ring network star, only bus meet the aboveconfigurations may mentioned functional requirements. Since responsiv~ness and fairness are, among other things, of primarily concern (or OCCS, the following criteria were chosen as the evaluation indices of industrial LAN. (a) Message transmission time (b) Waiting time and queue length message (c) System throughput (d) Channel utilization
of
All-Software Simulation Submodule (SSS) The SSS is a flexible all-software package which is capable of simulating time-slotted and token-controlled ring networks. By taking advantage of the all-software approach, the package is so designed that changes in simulation condition, i.e., exogenous and endogenous parameters, can be incorporated by simply modifying relevant input data. The parameters include: No. of nodes, physical distance between nodes, baud rate from node to line, message arrival and / Communical ion Processor
I
termination rates at nodes, line carrier frequency, average message length and their distribution, packet length, and No. of slots. Hybrid Hardware-Software Submodule(HSS)
Although the all-software approach could incorporate very detailed simulation models and realistic operating conditions in comparison with the queue-theoretic approach, it is very time-consuming if one wants to run the SSS for a wide variety of cases. In addition, the programming cost could be very high for detailed simulation models. The Hybrid Hardware-Software Simulation Submodule (HSS) has been developed to circumvent the above-mentioned shortcomings of SSS; it may be used for the complementary purpose to SSS. The HSS consists of a mimic (hardware) network capable of simulating realistically and flexibly various types of actual communication systems and an instrumentation system to collect and analyze the experimental data on the mimic network. Although the HSS is not so flexible as the SSS with regard to the dimensions and configurations of the communication system to be simulated, it has the advantage of less computing costs for simulation (Brayer and Lafleur, 1982). Another feature of the HSS lies in its capability of simulating various communication link characteristics and communication control protocols in more detail. Also, there is the posibility of imbedding a LAN controller LSI chip to simulate a specific communication protocol. As shown schematically in Fig. 1., the HSS physically consists of the five modules which follow. (a) Host Processor (HP) It serves as a man-machine interface of HSS and performs such function as setting of system
CP bus
Bbit
I
/Instrumentation Processor
,I
I P bus
8bit
!2-RAM 112-RAM p ort
p ort
!
1
!2-RAM 112-RAM 1-1
I
Node Processor
I
Ho s t Processor
I I
HP bus
Simulation
p ort
Po r
!
1
Node P rocesso r
,,8bit
q
I Delay
Se r i a I
Network
Fig. 1. System Configuration of HSS.
2671
Integrated Simulation System
parameters and simulation condi tions, displaying of results, and downsimulated loading of communication control programs to node processors.
base control system co nsisting of a host comp uter and multiple programable controllers . The effects of the number of PC's on the message transmission time were studied extensively.
(b) Control Processor (CP) The CP transfers to each node processor those messages specified by the HP such as arrival and termination of bit image communication messages on the basis of the user specified message length and arrival rate.
A large number of combinations of parameters were tested by using SSS and HSS for each of the above-mentioned cases. Each simu lation run was terminated when a total of 2,000 message s were received. Among other things, the following items were studied extensively.
(c) Instrumentati on Processor ( IP ) It collects the simulation data on the mimic network and sends them to HP.
(a) Effects of the number of slotts and of the packet length on the packet waiting time, the message transmission delay time and the channel and node utilizations under light, medium and heavy load traffics. (b) Slotted time vs single or multiple token schemes. (c) Use of a " short -cut" channel between a heavily-loaded pair of nodes. (d) Message queues and transmission delay time vs the number of stations involved (for Programmable Controller Network Model).
(d) Node Processors (NP) A node processor is provided for each of the stations. It transmits the message sent from CP according to the communication protocol specified by HP. (e) Artificial Communication Network (ACN) It is a mimic artificial ring network connecti ng the node processors. The inter-node distance is adjustable. A delay element is provided to simu late the transmission time between a pair of Node Processors. The communication protocol to be tested is written in an assembly language, which is assembled into a machine language program on the Host Processor and down-loaded to the respective Node Processors. The HSS can collect (1) message transmission time, (2) message waiting time, and (3) channel utilization. These statistical data are displayed on the CRT of the Host Processor.
SYSTEM MODULE
RELIABILITY
EVALUATION
Reliability, or more generally, RASIS, must be given the highest priority for any real-time computer control system. The System Reliability Evaluation Module (SREM) is a software package program with which to evaluate the overall system availability of DCCS. To be more specific, it can help the system designer evaluate quantitatively the effects of hardware failures, redundancies and maintainability on system availability. Use is made of Markovian chain models. DCCS Model for Reliability Evaluation
Cas es Studied The SSS and HSS have been successfully applied to three DCCS communication system models with different configurations. (a) Ring Network Reference Model This model se r ves as a reference model f o r comparative studies and consists of eight nodes, each two kilometers apart, with uniform message generation and termination rates. The communication protoco l s adopted are "time-slotted" and "token-controlled" (single and multiple tokens ). (b) Ring Network Model with Nonuniform Message Generationl Termination Rates (Goscinski and others, 1982) of the nonuniform message In vie w generationl termination rates, which is the case in most actual DCCS, a total of seven cases were studie d. (c) Programable Model This
model repre s ents
Controller
Network
a typical
sensor-
The DCCS model used for reliability evaluation consists of a number of DOe loop controllers or programmable logic controllers operating under the control of a supervisory controller, process inputl output devices, and operator consoles, all connected together by a communication net. For the purpose of enhancing system reliability, redundancy ( hardware back-up ) is oftentimes provided for the loop controllers and the network . Two system configurations shown in Fig. 2. (a) and ( b) were studied extensively, where the configuration (a) has process 110 unit and loop controller pairs distributedly located at each control led subsystem , with a sing le back-up loop control ler, while in the configuration (b) , the loop controllers are isolated from the process 110 units and a common back-up controller is provided in a concentrated fashion. In order to circumvent unnecessary complexities , the following assumptions are made in addition to conventional assumptions although some of which could be omitted or relaxed if desired. 1)
Process input lo utput fail.
units do not
H. Kasahara and S. Narita
2672
2) Failure and repair times obey Earlang exponential or distributions. 3) Failures are taken care of on a first - come - first - served basis by a single repairman. A total of eight models were constructed depending on the locations of redundant units, the repair time distribution, the success or failure of coverage, i.e., the probability of successful reconfiguration by disconnecting a faulty unit, and the number of repairman , with or without priorities. Methods of Analysis Three modules are provided for the reliability ana l ysis and evaluation of DCCS for each system configuration and each model described in the preceding section. The first module assumes exponential distributions for failure and repair times and employs the conventional Markovian chain approach (Kleinrock, 1975). The system availability can be calcu l ated by simply solving, a set of l inear simultaneous algebraic equations, i.e . the state transition equations . The second module is provided to account for non-exponential distributions for repair times and uses the so - called hidden Markovian chains (Nakagawa and Osaki, 1976). The last module employs an approximate models for rough but quick evaluation of system availability. Cases Studied The SREM program was run for a wide variety of parameter combinations. In particular, emphasis was placed on the following items. (a) Effects of MOT (Mean Down Time) and MTTR (Mean Time To Repair) of the
Network
(b) (c)
(d) (e)
controller of the network on system availability, with or without back up units . system Number of controllers vs availability . Effects of coverage (automatic or manual isolation of a faulty units, system recon - figulation, and system restoration) on system availab ili ty. Effects of additional back-up units. Effects of non-exponential (Ear l ang) repair time distributions . CONTROL MODULE
PERFORMANCE
EVALUATION
Prior to the implementation stage of DCCS, the system designer needs to check if the designed control system ca n successfully meet required specifications. More specifically, he may want to know, by some means, the excution time or response time of each functional software module as well as the utilization factor or computing load of each control computer under real - time, multi - task, multi - job operating conditions. Since no actual controlled system is yet available at the design stage of DCCS, the total controlled system or assembly of contro ll ed subsystems must be simulated by means of software or hardware . Several software packages have so far been developed which have the capability of simulating fairly large-scale controlled systems in realtime. For smaller control l ed systems, analog computers or dedicated analog -t ype simulators have been used . The latter approach is very suited for real-time simulation but suffers from disadvantages or shor t comings such as limited accuracies, scaling problems with respect to time and amplitude, and poor adaptability to large delay times and nonlinear elements . The former ( software ) approach essentially is very flexible except for its computation speed for real time simulation of large-scale control l ed systems having short time constants such as articulated robots and missile guidance systems. The problem of l imited computing speed of a mono-processor system could be reso l ved by the use of either a largescale mainframe with a high throughput rate or a parallel multiprocessor system, the latter approach being employed in the present integrated simulation scheme for its excellent cost-effectness . System Configuration
(a)
Network
S
Supervisory controller
C
Loop controller BC :Back-up (b)
Fig. 2. Two System Configurations of DCCS.
Fig. 3. shows the schematic of the CNPEM hardware, the main component being Host Processor (HP), Contro l Processor (CP), Operati on Processors (DP's) , two - port memory units for data transport between CP and OP ' s, and analog and digital input /output devices used to commun ic ate with the control computer(s) to be tested and other operations such as man - machine (CRT) operations . The HP takes care of such functions as inp ut, compile and store of the simulation source program written in the for m o f a block diagram or a set of differential algebraic equations representing dynamics of the controlled system. It also handles output of simulated results, analysis of the source programs, allocatio n and scheduling of res ultant tasks to OP's, and generation of
2673
Integrated Simulation System
macro instructions executable on CP and OP's. A sixteen-bit computer with a graphic display, a graphic printer and floppy disc units is employed as HP. The CP controls communication functions between HP and OP's such as down-loading of programs to OP's and transfer of simulated results back to HP. Each OP consists of an intel 8086/8087 pair and executes fundamental arithmetic operations, numerical integration and other mathematical operations such as trigonometric functions. Parallel Processing Algorithm The success or failure of any parallel processing scheme depends, among other things, on the careful allocation of the total computing load to the member processors so that the resultant overall computing time be minimized. The block diagram and relevant simulation conditions and parameters of the controlled system to be simulated is displayed on the CRT of HP by using the light pen and the keyboard. The HP then constructs the task graph ( directed acyclic graph, which represents precedence relation among the tasks and each task processing time) from the block diagram and allocates a set of tasks to each OP with due considerations given to precedence relations among the tasks and communication requirements among OP's. (A task is an elementary operation unit of analog computer simulation such as adder, multiplier, integrator, trigonometric function and square-rooter.) Since task scheduling problems of this type belong to the so-called NP-complete combinatorial problem (Coffman, 1976), a highly efficient heuristic algorithm was newly developed and embedded in the CNPEM (Kasahara and Narita, 1982; 1984). Cases Studied (Kasahara and Narita, 1983) The CNPEM was used to simulate a wide variety of controlled systems such as a train of mass-spring-damper elements for preliminary studies, an aircraft landing
on a flattop, and a seven d.o.f high-speed industrial robots. Thanks to the powerful multiprocessor scheduling algorithm and the high performance of i8086/8087 chips, large-scale controlled systems represented by several hundred tasks can be simulated in real time with a minimum number of parallel processors. CONCLUSION An integrated simulation system for the design and evaluation of distributed computer control sytems has been described. It can provide the system designer with a convenient vehicle with which to evaluate the three important ,facts of OCCS, i.e., communication, reliability and control performance, so that he can choose the best system architecture from many alternatives. The feature of the present simulation system lies in its use of combined softwarehardware approach to achieve the best overall economy and performance.
ACKNOWLEDGEMENT The authors wish to express their indebtedness to Mr. Akira Chuugo and Mr.Naoshi Wakatsuki who contributed to this work as their M.S. theses. This work was supported in part by the Ministry of Education through the Grant No.(c) 58550253.
REFERENCES Brayer, k., and V. Lafieur (1982). A Test Bed Approarch to Design of a Computer Communication Network. IEEE. Computer, 12, 14-23. Coffman, E. G. (1976). Job-Shop Scheduling Theory. John Wiley & Sons. Goscinski, A., and others (1982). Ring Computer Networks for Real Time Process Control. Proc. of 4th IFAC Press Workshop on DCCS. Pergamon pp.167-177.
-----,
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I
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Control
I
~ .Lo.!TI..P)l.! ~.!:-~ I
Graphic Display
Floppy Disc
Graphic Printer
• • • Fig. 3. CNPEM Hardware Configuration.
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2674
H. Kasahara and S. Narita
Harrison, T. J. (1982). IEEE Project 802: Local Area Network Standard. ~ of 4th IFAC Workshop on OCCS. Pergamon Press, pp.13-24. Kasahara, H., and S. Narita (1982). Parallel Processing Real-Time Control and Simulation of OCCS. Proc. of 4th IFAC Workshop on DCCS. Pergamon Press, pp.103-113. Kasahara, H., and S. Narita (1983). Parallel Processing Scheme for MultiProcessor Continuous System Simulation. J. of Japan Society for Simulation Technology, 1, 142-151. Kasahara, H., and S. Narita (1984). Load Distribution among Real-Time Control Computers Connected via Communication Media. 9th IFAC Triennial World Congress. (Colloquium No.4,2 "Communication for".) Kleinrock, L. (1975). Queing Systems. J.Willy and Sons. Nakagawa, H., and S. Osaki (1976). Markov Processes with Some NonRenewal Reguration Points and Their Apprication to Reliability Theory. Microelectron. Reliab., 12., 633-639.
COI)\ri .~Il(
INTEGRA TED SIMULATION SYSTEM FOR DESIGN AND EVALUATION OF DISTRIBUTED COMPUTER CONTROL SYSTEMS H. Kasahara and S. Narita De/mrtme1l1 of Electrical Engi1U'ering. l\'asl'da L'nil 1f'rsily. Tokyu 160. Japan
Abstract. This paper presents an integrated simulation system to be used for the design and evaluation of distributed computer control systems. The simulation system is comprised of Communication Performance Evaluation Module, System Reliability Evaluation Module and Control Performance Evaluation Module. Different from conventional all-software approaches, dedicated hardware facilities such as a parallel multimicroprocessor system for real-time simulation of controlled system dynamics and a mimic communication system are used advantageously to achieve best overall economy of simulation in conjunction with software simulation modules. The features of the proposed of simulation system as applied to several dfstributed computer control systems with different system architectures are described. Keywords. Computer control; Markov processes; Network analysers; Parallel processing; Reliability thory; Local area network; Simulation; Distributed computer control systems.
OVERVIEW OF INTEGRATED SIMULATION SYSTEM
COMMUNICATION PERFORMANCE EVALUATION MODULE
This paper presents an integrated simulation system to be used for the design and analysis stages of Distributed Computer Control Systems (DCCS). A variety of evaluation criteria are involved and must be duly taken into account to implement DCCS, which typically is made up of multiple computers or nodes interconnected by some communication net. Among other evaluation criteria, communication performance, system reliability and control performance may be considered the triumvirate. The present simulation system is aimed at the integrated evaluation of the aforementioned criteria and comprised of the following modules .
The Communication Performance Evaluation Module (CMPEM) is a simulation module to be used for the evaluation of communication performance of DCCS. It is broken down into the following submodules. (a)
(b)
5.5.5:
All-software simulation submodule written in GPSS (General- Purpose Simulation System) . H.S.S: Hybrid hardware-software simulation submodule.
The former simulation submodule is suited for rough or detailed evaluation of a wide variety of communication systems with possibly different configurations, dimensions, transmission rates and communication protocols. In this sense, it is provided with more flexibility than the latter submodule, which may be used to advantage for more cost-effective evaluation of specific communication nets. Emphasis is placed on the evaluation of the communication performance of local area networks (LAN) such as IEEE Project 802 (Harrison, 1982) as they are used in real-time control environments because few contributions have so far been reported to the potential capabilities of LAN in industrial environments (factory 3utomation, for example).
(1) Communication Performance Evaluation Module(CMPEM). (2) System Reliability Evaluation Module (SREM) . (3) Control Performance Evaluation Module(CNPEM). here stands for A module as defined either an all-software simulation package or a combination of specific software and dedicated hardware to perform jointly a specific simulation function. Different from all-software evaluation systems or hardware-oriented testbeds of DCCS, use is made of the hybrid (joint hardware-software) approach to take advantage of the inherent features of hardware and software . In what follows, the function, configuration and features of each of the above-mentioned modules are described in detail.
The authors would like to add that they purposely avoided the use of the queuetheoretic approach except for the validation check of the simulation results since the formulae derived on the basis of queuing theory only apply to a few idealized cases, e.g., simplified communication protocols, uniform message 2669
H. Kasahara and S. Narita
2670
generation and destination distributions. Functional Requirements and Criteria of Industrial LAN
Evaluation
When a local area network is to be applied to industrial real-time control, the following functions must be duly taken into consideration: (a) Responsiveness (real-time capabilities) (b) Fairness (n-to-n communication) (c) High data transmission rate (d) Expandability (e) High reliability and maintainability variety of LAN Among a wide configurations such as bus, ring, and and ring network star, only bus meet the aboveconfigurations may mentioned functional requirements. Since responsiv~ness and fairness are, among other things, of primarily concern (or OCCS, the following criteria were chosen as the evaluation indices of industrial LAN. (a) Message transmission time (b) Waiting time and queue length message (c) System throughput (d) Channel utilization
of
All-Software Simulation Submodule (SSS) The SSS is a flexible all-software package which is capable of simulating time-slotted and token-controlled ring networks. By taking advantage of the all-software approach, the package is so designed that changes in simulation condition, i.e., exogenous and endogenous parameters, can be incorporated by simply modifying relevant input data. The parameters include: No. of nodes, physical distance between nodes, baud rate from node to line, message arrival and / Communical ion Processor
I
termination rates at nodes, line carrier frequency, average message length and their distribution, packet length, and No. of slots. Hybrid Hardware-Software Submodule(HSS)
Although the all-software approach could incorporate very detailed simulation models and realistic operating conditions in comparison with the queue-theoretic approach, it is very time-consuming if one wants to run the SSS for a wide variety of cases. In addition, the programming cost could be very high for detailed simulation models. The Hybrid Hardware-Software Simulation Submodule (HSS) has been developed to circumvent the above-mentioned shortcomings of SSS; it may be used for the complementary purpose to SSS. The HSS consists of a mimic (hardware) network capable of simulating realistically and flexibly various types of actual communication systems and an instrumentation system to collect and analyze the experimental data on the mimic network. Although the HSS is not so flexible as the SSS with regard to the dimensions and configurations of the communication system to be simulated, it has the advantage of less computing costs for simulation (Brayer and Lafleur, 1982). Another feature of the HSS lies in its capability of simulating various communication link characteristics and communication control protocols in more detail. Also, there is the posibility of imbedding a LAN controller LSI chip to simulate a specific communication protocol. As shown schematically in Fig. 1., the HSS physically consists of the five modules which follow. (a) Host Processor (HP) It serves as a man-machine interface of HSS and performs such function as setting of system
CP bus
Bbit
I
/Instrumentation Processor
,I
I P bus
8bit
!2-RAM 112-RAM p ort
p ort
!
1
!2-RAM 112-RAM 1-1
I
Node Processor
I
Ho s t Processor
I I
HP bus
Simulation
p ort
Po r
!
1
Node P rocesso r
,,8bit
q
I Delay
Se r i a I
Network
Fig. 1. System Configuration of HSS.
2671
Integrated Simulation System
parameters and simulation condi tions, displaying of results, and downsimulated loading of communication control programs to node processors.
base control system co nsisting of a host comp uter and multiple programable controllers . The effects of the number of PC's on the message transmission time were studied extensively.
(b) Control Processor (CP) The CP transfers to each node processor those messages specified by the HP such as arrival and termination of bit image communication messages on the basis of the user specified message length and arrival rate.
A large number of combinations of parameters were tested by using SSS and HSS for each of the above-mentioned cases. Each simu lation run was terminated when a total of 2,000 message s were received. Among other things, the following items were studied extensively.
(c) Instrumentati on Processor ( IP ) It collects the simulation data on the mimic network and sends them to HP.
(a) Effects of the number of slotts and of the packet length on the packet waiting time, the message transmission delay time and the channel and node utilizations under light, medium and heavy load traffics. (b) Slotted time vs single or multiple token schemes. (c) Use of a " short -cut" channel between a heavily-loaded pair of nodes. (d) Message queues and transmission delay time vs the number of stations involved (for Programmable Controller Network Model).
(d) Node Processors (NP) A node processor is provided for each of the stations. It transmits the message sent from CP according to the communication protocol specified by HP. (e) Artificial Communication Network (ACN) It is a mimic artificial ring network connecti ng the node processors. The inter-node distance is adjustable. A delay element is provided to simu late the transmission time between a pair of Node Processors. The communication protocol to be tested is written in an assembly language, which is assembled into a machine language program on the Host Processor and down-loaded to the respective Node Processors. The HSS can collect (1) message transmission time, (2) message waiting time, and (3) channel utilization. These statistical data are displayed on the CRT of the Host Processor.
SYSTEM MODULE
RELIABILITY
EVALUATION
Reliability, or more generally, RASIS, must be given the highest priority for any real-time computer control system. The System Reliability Evaluation Module (SREM) is a software package program with which to evaluate the overall system availability of DCCS. To be more specific, it can help the system designer evaluate quantitatively the effects of hardware failures, redundancies and maintainability on system availability. Use is made of Markovian chain models. DCCS Model for Reliability Evaluation
Cas es Studied The SSS and HSS have been successfully applied to three DCCS communication system models with different configurations. (a) Ring Network Reference Model This model se r ves as a reference model f o r comparative studies and consists of eight nodes, each two kilometers apart, with uniform message generation and termination rates. The communication protoco l s adopted are "time-slotted" and "token-controlled" (single and multiple tokens ). (b) Ring Network Model with Nonuniform Message Generationl Termination Rates (Goscinski and others, 1982) of the nonuniform message In vie w generationl termination rates, which is the case in most actual DCCS, a total of seven cases were studie d. (c) Programable Model This
model repre s ents
Controller
Network
a typical
sensor-
The DCCS model used for reliability evaluation consists of a number of DOe loop controllers or programmable logic controllers operating under the control of a supervisory controller, process inputl output devices, and operator consoles, all connected together by a communication net. For the purpose of enhancing system reliability, redundancy ( hardware back-up ) is oftentimes provided for the loop controllers and the network . Two system configurations shown in Fig. 2. (a) and ( b) were studied extensively, where the configuration (a) has process 110 unit and loop controller pairs distributedly located at each control led subsystem , with a sing le back-up loop control ler, while in the configuration (b) , the loop controllers are isolated from the process 110 units and a common back-up controller is provided in a concentrated fashion. In order to circumvent unnecessary complexities , the following assumptions are made in addition to conventional assumptions although some of which could be omitted or relaxed if desired. 1)
Process input lo utput fail.
units do not
H. Kasahara and S. Narita
2672
2) Failure and repair times obey Earlang exponential or distributions. 3) Failures are taken care of on a first - come - first - served basis by a single repairman. A total of eight models were constructed depending on the locations of redundant units, the repair time distribution, the success or failure of coverage, i.e., the probability of successful reconfiguration by disconnecting a faulty unit, and the number of repairman , with or without priorities. Methods of Analysis Three modules are provided for the reliability ana l ysis and evaluation of DCCS for each system configuration and each model described in the preceding section. The first module assumes exponential distributions for failure and repair times and employs the conventional Markovian chain approach (Kleinrock, 1975). The system availability can be calcu l ated by simply solving, a set of l inear simultaneous algebraic equations, i.e . the state transition equations . The second module is provided to account for non-exponential distributions for repair times and uses the so - called hidden Markovian chains (Nakagawa and Osaki, 1976). The last module employs an approximate models for rough but quick evaluation of system availability. Cases Studied The SREM program was run for a wide variety of parameter combinations. In particular, emphasis was placed on the following items. (a) Effects of MOT (Mean Down Time) and MTTR (Mean Time To Repair) of the
Network
(b) (c)
(d) (e)
controller of the network on system availability, with or without back up units . system Number of controllers vs availability . Effects of coverage (automatic or manual isolation of a faulty units, system recon - figulation, and system restoration) on system availab ili ty. Effects of additional back-up units. Effects of non-exponential (Ear l ang) repair time distributions . CONTROL MODULE
PERFORMANCE
EVALUATION
Prior to the implementation stage of DCCS, the system designer needs to check if the designed control system ca n successfully meet required specifications. More specifically, he may want to know, by some means, the excution time or response time of each functional software module as well as the utilization factor or computing load of each control computer under real - time, multi - task, multi - job operating conditions. Since no actual controlled system is yet available at the design stage of DCCS, the total controlled system or assembly of contro ll ed subsystems must be simulated by means of software or hardware . Several software packages have so far been developed which have the capability of simulating fairly large-scale controlled systems in realtime. For smaller control l ed systems, analog computers or dedicated analog -t ype simulators have been used . The latter approach is very suited for real-time simulation but suffers from disadvantages or shor t comings such as limited accuracies, scaling problems with respect to time and amplitude, and poor adaptability to large delay times and nonlinear elements . The former ( software ) approach essentially is very flexible except for its computation speed for real time simulation of large-scale control l ed systems having short time constants such as articulated robots and missile guidance systems. The problem of l imited computing speed of a mono-processor system could be reso l ved by the use of either a largescale mainframe with a high throughput rate or a parallel multiprocessor system, the latter approach being employed in the present integrated simulation scheme for its excellent cost-effectness . System Configuration
(a)
Network
S
Supervisory controller
C
Loop controller BC :Back-up (b)
Fig. 2. Two System Configurations of DCCS.
Fig. 3. shows the schematic of the CNPEM hardware, the main component being Host Processor (HP), Contro l Processor (CP), Operati on Processors (DP's) , two - port memory units for data transport between CP and OP ' s, and analog and digital input /output devices used to commun ic ate with the control computer(s) to be tested and other operations such as man - machine (CRT) operations . The HP takes care of such functions as inp ut, compile and store of the simulation source program written in the for m o f a block diagram or a set of differential algebraic equations representing dynamics of the controlled system. It also handles output of simulated results, analysis of the source programs, allocatio n and scheduling of res ultant tasks to OP's, and generation of
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macro instructions executable on CP and OP's. A sixteen-bit computer with a graphic display, a graphic printer and floppy disc units is employed as HP. The CP controls communication functions between HP and OP's such as down-loading of programs to OP's and transfer of simulated results back to HP. Each OP consists of an intel 8086/8087 pair and executes fundamental arithmetic operations, numerical integration and other mathematical operations such as trigonometric functions. Parallel Processing Algorithm The success or failure of any parallel processing scheme depends, among other things, on the careful allocation of the total computing load to the member processors so that the resultant overall computing time be minimized. The block diagram and relevant simulation conditions and parameters of the controlled system to be simulated is displayed on the CRT of HP by using the light pen and the keyboard. The HP then constructs the task graph ( directed acyclic graph, which represents precedence relation among the tasks and each task processing time) from the block diagram and allocates a set of tasks to each OP with due considerations given to precedence relations among the tasks and communication requirements among OP's. (A task is an elementary operation unit of analog computer simulation such as adder, multiplier, integrator, trigonometric function and square-rooter.) Since task scheduling problems of this type belong to the so-called NP-complete combinatorial problem (Coffman, 1976), a highly efficient heuristic algorithm was newly developed and embedded in the CNPEM (Kasahara and Narita, 1982; 1984). Cases Studied (Kasahara and Narita, 1983) The CNPEM was used to simulate a wide variety of controlled systems such as a train of mass-spring-damper elements for preliminary studies, an aircraft landing
on a flattop, and a seven d.o.f high-speed industrial robots. Thanks to the powerful multiprocessor scheduling algorithm and the high performance of i8086/8087 chips, large-scale controlled systems represented by several hundred tasks can be simulated in real time with a minimum number of parallel processors. CONCLUSION An integrated simulation system for the design and evaluation of distributed computer control sytems has been described. It can provide the system designer with a convenient vehicle with which to evaluate the three important ,facts of OCCS, i.e., communication, reliability and control performance, so that he can choose the best system architecture from many alternatives. The feature of the present simulation system lies in its use of combined softwarehardware approach to achieve the best overall economy and performance.
ACKNOWLEDGEMENT The authors wish to express their indebtedness to Mr. Akira Chuugo and Mr.Naoshi Wakatsuki who contributed to this work as their M.S. theses. This work was supported in part by the Ministry of Education through the Grant No.(c) 58550253.
REFERENCES Brayer, k., and V. Lafieur (1982). A Test Bed Approarch to Design of a Computer Communication Network. IEEE. Computer, 12, 14-23. Coffman, E. G. (1976). Job-Shop Scheduling Theory. John Wiley & Sons. Goscinski, A., and others (1982). Ring Computer Networks for Real Time Process Control. Proc. of 4th IFAC Press Workshop on DCCS. Pergamon pp.167-177.
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Graphic Display
Floppy Disc
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• • • Fig. 3. CNPEM Hardware Configuration.
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H. Kasahara and S. Narita
Harrison, T. J. (1982). IEEE Project 802: Local Area Network Standard. ~ of 4th IFAC Workshop on OCCS. Pergamon Press, pp.13-24. Kasahara, H., and S. Narita (1982). Parallel Processing Real-Time Control and Simulation of OCCS. Proc. of 4th IFAC Workshop on DCCS. Pergamon Press, pp.103-113. Kasahara, H., and S. Narita (1983). Parallel Processing Scheme for MultiProcessor Continuous System Simulation. J. of Japan Society for Simulation Technology, 1, 142-151. Kasahara, H., and S. Narita (1984). Load Distribution among Real-Time Control Computers Connected via Communication Media. 9th IFAC Triennial World Congress. (Colloquium No.4,2 "Communication for".) Kleinrock, L. (1975). Queing Systems. J.Willy and Sons. Nakagawa, H., and S. Osaki (1976). Markov Processes with Some NonRenewal Reguration Points and Their Apprication to Reliability Theory. Microelectron. Reliab., 12., 633-639.