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AI in control Systems engineering

Published online by Cambridge University Press:  07 July 2009

D. A. Linkens
D. A. Linkens
Affiliation:
Department of Control Engineering, University of Sheffield, Sheffield, UK
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Abstract

Decision-making is an integral part of any consideration of the discipline of control Systems. This implies feedback of knowledge in some format, whether it is mediated via human or machineoriented methods. The application of AI methodologies to control Systems engineering is described in this review under two broad categories of design and implementation. The design of control strategies is itself divided into phases of modelling and simulation, identification, and algorithm selection and tuning. The aspects of implementation which are covered include real-time considerations such as knowledge-based control and fuzzy logic, multi-sensor data fusion, fault detection and Human–Computer Interaction (HCI).

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Type
Research Article
Information
The Knowledge Engineering Review , Volume 5 , Issue 3 , September 1990 , pp. 181 - 214
Copyright
Copyright © Cambridge University Press 1990

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References

Araki, M, 1985. “Industrial applications in Japan in CAD packages for control Systems” IFAC Symp. Lyngby, pp 71–76.Google Scholar
Arzen, KE, 1988. “An architecture for expert system based feedback control” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 15–20.Google Scholar
Assilian, S and Mamdani, EH, 1975. “An experiment in linguistic synthesis with a fuzzy logic controller” Int. J. Man-Machine Systems 7 pp 1–13.Google Scholar
Astrom, KJ, Anton, JJ and Arzen, KE, 1986. “Expert Control” Automatica 22 (3) pp 277–286.CrossRefGoogle Scholar
Astrom, KJ and Kreutzer, W, 1986. “System representations” In Proc. IEEE Control Systems Soc., 3rd Symp. on CACSD, Arlington, Virginia, pp 24–26.Google Scholar
Barker, HA, Chen, M, Grant, PW, Jobling, CP and Townsend, P, 1986. “A graphical pre-processor for computer-aided control system design. Inst MC Workshop” Computer-Aided Control System Design, Salford, pp 15–20.Google Scholar
Bekey, GA, 1988. “Knowledge based Systems in modelling simulation and identification” IFAC Symp. on Sys. Ident., Beijing.Google Scholar
Bennett, S, Rahbar, M, Linkens, DA, Tanyi, E and Smith, M, 1989. “A Knowledge-based Environment for Modelling and Simulation (KEMS)” MULTI'89 Simulation Conference,San Diego.Google Scholar
Betta, A and Linkens, DA, 1988. “EASI (Expert Advisor for System Identification): A prototype package for linear and non-linear system” Control'88, Oxford.Google Scholar
Betta, A and Linkens, DA, 1990. “Intelligent knowledge-based system for dynamic system identification” in Proc IEE Pt D, Vol 137, Pt D, pp 1–12.CrossRefGoogle Scholar
Beutler, KP, 1988. “The Descriptive search to realize a knowledge-based retrieval of reusable project results” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 119–122.Google Scholar
Billings, SA, Fadzil, MB, Voon, WSF and Leontaritis, IJ, 1984. User Reference Manual of NLI: Nonlinear Identification Package, Dept. of Control. Eng., University of Sheffield.Google Scholar
Borchardt, GC, 1986. “STAR: A computer language for hybrid AI applications” In Coupling Symbolic and Numerical Computing in Expert Systems (ed. Kowalik), Elsevier: Amsterdam, pp 169–177.Google Scholar
Borgida, A, Greenspan, S and Mylopoulos, J, 1985. “A knowledge representation as the basis for requirements specification” IEEE Computer, pp 82–91.CrossRefGoogle Scholar
Brown, PJ, 1986. “Interactive documentation”. Software Practice & Experience, 16, No 3, pp 291–299.Google Scholar
Clare, J, 1989. “Real-time application of advanced control in industry” ISA '89 Advanced Control Conference,NEC,Birmingham, pp 10.1–10.9.Google Scholar
Cohen, PR and Feigenbaum, E, 1982. “MOLGEN” In The Handbook of Artificial Intelligence, Vol. 3, Los Altos, CA: William Kaufman Publishing, pp 551–556.Google Scholar
Dearden, H, 1989. “Application of self-tuning control for process plant optimization” ISA '89 Advanced Control Conference,NEC,Birmingham, pp 4.1–4.14.Google Scholar
di, Primio and Brewska, G, 1985. “BABYLON: kernel System of an integrated environment for expert System development and operation” In Proc. 5th Int Workshop on Expert Systems and their Application, Avignon, pp 573–583.Google Scholar
Elzer, P, Borchers, HW, Weisang, C and Zinser, R, 1988. “Knowledge-supported generation of control room pictures” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 129–136.Google Scholar
Epton, J, 1989. “Adaptive and self-tuning controllers: an overview” ISA '89 Advanced Control Conference,NEC,Birmingham, pp 2.1–2.11.Google Scholar
Erman, LD, Hayes-Roth, F, Lesser, VR and Reddy, DR, 1988. “The Hearsay-II Speech-Understanding System: integrating knowledge to resolve uncertainty” In Blackboard Systems (ed. Engelmore, R and Morgan, R), New York: Addison Wesley.Google Scholar
Fjellheim, RA, 1986. “A knowledge based interface to process simulation” In AI Applied to Simulation (ed. Vansteenkiste, Kerckhoffs and Ziegler, ), Simulation Series, Vol. 18, no. 1, Feb, SCS: California, pp 97–102.Google Scholar
Fortuna, L, Nunnari, G, Vassallo, F and Zuccarini, P, 1988. “An educational tool for control System design: Why an expert System? In Trends in Control and Measurement Education, IFAC Symp., Swansea, pp 207–212.Google Scholar
Francis, JC and Leitch, RR, 1984. “ARTIFACT: A real-time shell for intelligent feedback control” In Proc. British Computer Soc. Conf. Expert Systems '84, also in Research and Development in Expert Systems (ed. Bramer, ), Cambridge University Press: Cambridge, pp 151–163.Google Scholar
Gallant, M, Guida, G, Spampinato, L and Stefanini, A, 1985. “Representing procedural knowledge in expert Systems: An application to process control” In Proc. 9th Int. Joint Conf. on AI, pp 345–352.Google Scholar
Gladd, NT and Krall, NA, 1986. “Artificial intelligence methods for facilitating large-scale numerical computations” In Coupling Symbolic and Numerical Computing in Expert Systems (ed. Kowalik, ), Amsterdam: Elsevier, pp 123–136.Google Scholar
Haest, M, Bastin, G, Gevers, M and Wertz, V, 1988. “An expert System for System identification IFAC Workshop on AI in Real-time Control, Swansea, pp 101–106.Google Scholar
Hamiane, D and Morris, AS, 1985. Linear Multivariable Identification Package, University of Sheffield: Dept. of Control Eng.Google Scholar
Harris, CJ and Read, AB, 1988. “Knowledge based fuzzy motion control of autonomous vehicles” In Artificial Intelligence in Real-time Control, IFAC Workshop, Swansea, pp 149–154.Google Scholar
Haspel, D, 1989. “The use of an expert System for cement manufacture” ISA '89 Advanced Control Conference,NEC,Birmingham, pp 8.1–1.9.Google Scholar
Haton, JP, 1983. “Knowledge-based and expert Systems in industrial applications” IFAC Workshop on Artificial Intelligence, Leningrad, pp 83–89.Google Scholar
lonescu, D, 1988. “An expert System with a learning mechanism for real time process control” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 27–40.Google Scholar
Jacob, F, Suslenschi, P and Vernet, D, 1986. “EXTASE: An expert System for alarm processing in process control” Proc. 7th Eur. Conf. on AI, Vol. 2, pp 103–108.Google Scholar
James, JR, Frederick, DK, Bonissone, PP and Taylor, JH, 1985a. “A retrospective view of CACE-III: Considerations in co-ordinating symbolic and numeric computaton in a rule-based expert System” 2nd Conf. on AI Applications: The Eng. of Knowledge-based Systems. Washington: IEEE Computer Soc. Press, pp 532–538.Google Scholar
James, JR, Taylor, JH and Frederick, DK, 1985b. “An expert System architecture for coping with complexity in computer-aided control engineering” 3rd IFAC/IFIP Int. Symp. CADCE '85, Lyngby.Google Scholar
Karwatzki, JM, 1987. “An expert system for monitoring helicopter airworthiness” Measurement and Control 20 pp 112–114.CrossRefGoogle Scholar
Kolseki, C, Van, Daele, Millot, P and de Keyser, V, 1988. “Towards an intelligent editor of industrial control views using rules for ergonomic design” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 137–142.Google Scholar
Krigsman, AJ, Verbruggen, HB and Bruijn, M, 1988. “Knowledge-based real-time control” IFAC Workshop on “AI in Real-time Control”, Swansea, pp 7–13.Google Scholar
Langen, PA, 1987. “Application of artificial intelligence techniques to simulation” In Simulation and Al (ed. Luker, and Birtwistle, ), Simulation Series, Vol. 18, no. 3, SCS: California, pp 49–57.Google Scholar
Larsson, JE and Persson, P, 1988. “The knowledge database used in an expert System interface for IDPAC” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 107–112.Google Scholar
Lehman, A, 1987. “Expert Systems for interactive simulation of computer System dynamics” In Simulation and AI (ed. Luker, and Birtwistle, ). Simulation Series, Vol. 18, no. 3, SCS: California, pp 21–26.Google Scholar
Lehman, A, Knodler, B, Kwee, E and Szczerbicka, H, 1986. “Dialogue-oriented and knowledge-based modelling in a typical PC environment” In AI Applied to Simulation (ed. Kerckhoffs, , Vansteenkiste, and Ziegler, ), Simulation Series, Vol. 18, no. 1, SCS: California, pp 91–96.Google Scholar
Leitch, R and Dulieu, MRW, 1987. “RESCU REVISITED—A review of a practical real-time expert System” In Research and Development in Expert Systems (ed. Moralee, ), Cambridge: Cambridge University Press, pp 267–276.Google Scholar
Linkens, DA, 1988. “Control System design: a survey of personal computer software” Trans. Inst. MC, 10(5) pp 240–257.CrossRefGoogle Scholar
Linkens, DA, Greenhow, SG and Asbury, AJ, 1986. “An expert System for the control of depth of anaesthesia” Biomed. Meas. Info. Contr., 1(4) pp 223–228.Google Scholar
Linkens, DA and Hasnain, SB, 1989. “Self-organising Systems and their transputer implementation” In Parallel Processing and Artificial Intelligence (ed. Reeve, M & Zenith, SV), Chichester: Wiley, pp 249–247.Google Scholar
Linkens, DA and Manfouf, M, 1988. “Fuzzy logic knowledge-based control for muscle relaxant anaesthesia” IFAC Modelling and Control in Biomedical Systems, Venice, pp 185–190.Google Scholar
Lounamaa, P and Tse, E, 1986. The Simulation and Expert Environment in Coupling Symbolic and Numerical Computing in Expert Systems (ed. Kowalik, ), Amsterdam: Elsevier, pp 83–100.Google Scholar
Maciejowski, JM, 1985. “A core data model for computer-aided control engineering” Cambridge University Eng. Dept. Tech. Report CUED/F-CAMS/TR257.Google Scholar
Maciejowski, JM, 1988. “Data structures and software tools for CACSD: A survey” IFAC Symposium, CACSD, Beijing.Google Scholar
Mason, A, 1989. “Practical implementation of large real-time expert Systems for process and plant management” ISA '89 Advanced Control Conference,NEC,Birmingham, pp 11.1–11.16.Google Scholar
Moore, RL, 1989. “Application of the real-time expert Systems in the US” ISA '89 Advanced Control Conference,NEC,Birmingham, pp 11.1–11.16.Google Scholar
Munro, N, Palaskas, Z and Frederick, DK, 1986. “An adaptive CACSD dialogue facility” In IEE 3rd Symp. on Computer-Aided Control System Design (ed. Lineberry, ), New York, Arlington, VA: IEEE, pp 146–149.Google Scholar
Neilson, NR, 1987. “The impact of using AI-based techniques in a control System Simulator” In Simulation and AI (ed. Luker, and Birtwistle, ), Simulation Series, Vol. 18, no. 3, SCS: California, pp 72–77.Google Scholar
Ogard, O and Wood, E, 1988. “Intelligent alarm handling” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 69–74.Google Scholar
Pang, GKH and Boyle, J -M, 1986. “An expert System for analytical and interactive design of control Systems” Expert Systems '86, Cambridge.Google Scholar
Pang, GKH and MacFarlane, AGJ, 1987. “An expert Systems approach to CAD of multivariable Systems” In Lecture Notes in Control and Information Sciences, New York: Springer-Verlag.Google Scholar
Pave, A and Rechenmann, F, 1986. “Computer-aided modelling in biology: An artificial intelligence approach” In AI Applied to Simulation (ed. Kerckhoffs, , Vansteenkiste, and Ziegler, ), Simulation Series, Vol. 18, no. 1, SCS: California, pp 52–66.Google Scholar
Permantier, G, 1988. “Representation of inexact engineering knowledge about real time Systems” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 41–46.Google Scholar
Procyk, TJ and Mamdani, EH, 1979. “A linguistic self-organising process controller” Automatica, 15 pp 15–30.CrossRefGoogle Scholar
Rahbar, MT, Bennett, S and Linkens, DA, 1987. “Functional specification of an intelligent simulation environment” UKSC '87 Conf. on Computer Simulation, Bangor, pp 187–192.Google Scholar
Rahbar, MT, Bennett, S, Linkens, DA and Thompson, B, 1989. “A integrated database: ils role in a knowledge-based environment for modelling and simulation (KEMS)” ESC '89 3rd Euro Congress, Edinburgh.Google Scholar
Rajagopalan, R, 1986. “Qualitative modelling and simulation: A survey” In AI Applied to Simulation (ed. Kerckhoffs, , Vansteenkiste, and Ziegler, ), Simulation Series, Vol. 18, no. 1, SCS: California, pp 9–26.Google Scholar
Ranganathan, SR, 1957. Colon Classification, London: Madras Library Association.Google Scholar
Rao, M and Jiang, T-S, 1989. “Real-time intelligent control” Engineering Application of Artificial Intelligence.Google Scholar
Rasmussen, J and Goodstein, LP, 1985. “Decision support in supervisory control” IFAC Congress on Analysis, Design and Evaluation of Man–Machine Systems, Varese, Italy.Google Scholar
Reilly, DP and Timberlake, AI, 1987. “Intelligent front-end to Box and Jenkins forecasting” In Interactions in AI and Statistical Methods (ed. Phelps, B), Technical Press, Unicom Seminars Ltd.Google Scholar
Rimvall, M, 1988. “Interactive environments for CACSD software” IFAC Symp on CACSD, Beijing, China.Google Scholar
Rimvall, M and Bomholt, L, 1985. “A flexible man–machine interface for CACSD applications” Preprints of 3rd IFAC/IFIP Int. Symp. on CAD in Control and Eng. Syst., Copenhagen, Denmark.Google Scholar
Sacks, PH, Patterson, AM and Tunes, MHM, 1986. “ESCORT: An expert System for complex operations in real-time” Expert Systems, 3(1).Google Scholar
Sanoff, SP and Wellstead, PE, 1985. “Expert identification and control” IFAC Conf. Ident. and Syst. Parameter Estimation, York, pp 1273–1278.Google Scholar
Sugeno, M, 1985. Industrial Applications of Fuzzy Control, Amsterdam: North Holland.Google Scholar
Tanyi, E and Linkens, DA, 1987. “A frame-based modelling and simulation environment” UKSC '87 Conf. on Computer Simulation, Bangor.Google Scholar
Tanyi, E and Linkens, DA, 1989. “Addition of a knowledge acquisition facility to a knowledge-based environment for modelling and simulation (KEMS)” ESC '89 Advanced Control Congress, Edinburgh.Google Scholar
Taunton, C, 1989. “Expert Systems in process control: an overview” ISA '89 Advanced Control Conference,NEC,Birmingham, pp 5.1–5.5.Google Scholar
Taylor, JH, 1987. “Conventional and expert-aided database management for computer-aided control engineering” In Proc. Amer. Cont. Conf., ACC.Google Scholar
Taylor, JH and Frederick, DK, 1984. “Expert Systems architecture for computer-aided control engineering” In Proc. Amer. Cont. Conf., ACC.Google Scholar
Tetley, B and Ulf, A, 1989. “Self-tuning and gain scheduling for process control” ISA '89 Advanced Control Conference,NEC,Birmingham, pp 5.1–5.5.Google Scholar
Thomson, AC, 1988. “Real-time artificial intelligence for process monitoring and control” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 89–94.Google Scholar
Togai, M and Watanabe, H, 1985. “A VLSI implementation of fuzzy inference engine: toward an expert System on a chip” New York: IEEE, pp 192–197.Google Scholar
Tong, RM, 1977. “A control engineering review of fuzzy Systems” Automatica, 13 pp 559–569.CrossRefGoogle Scholar
Trankle, TL and Markosian, LZ, 1985. “An expert System for control System design” In Control '85 IEE Conf., Cambridge, pp 495–499.Google Scholar
Tsang, TTC and Billings, SA, 1987. FASTNOI: Fast Nonlinear Orthogonal Identification, University of Sheffield: Dept. of Control Eng.Google Scholar
Van den Bosch, PPJ and Van den Boom, AJW, 1985. “Industrial application in the Netherlands for CAD packages in control Systems” IFAC Symp., Lyngby, pp 58–61.Google Scholar
Vingerhoeds, RA, Delbar, P and Boullart, L, 1988. “Expert Systems for process control using automatic knowledge acquisition” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 57–62.Google Scholar
Voss, H, 1988. “Architectural issues for expert Systems in real-time control” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansa, pp 1–6.Google Scholar
Wagner, B, 1988. “Knowledge-based constraint specification in the development of process automation Systems” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 113–118.Google Scholar
West, AA, Chandraker, R, Williams, DJ and Mulvaney, DJ, 1988. “Hybrid representation of real-time control rules for manufacturing process control in electronics manufacture” IEEE Symp. Intelligent Control, Arlington, Virginia.Google Scholar
Zadeh, LA, 1965. “Fuzzy sets” Info, and Control I, pp 338–353.Google Scholar
Ziegler, BP, 1976. Theory of Modelling and Simulation, New York: Wiley.Google Scholar
Ziegler, BP and De Wael, L (1986). “Towards a knowledge-based implementation of multifaceted modelling methodology” In AI Applied to Simulation (ed. Kerckhoffs, , Vansteenkiste, and Ziegler, ), Simulation Series, Vol. 18, no. 1, SCS: California, pp 42–51.Google Scholar
Zhang, L, Cameron, RG, Ammour, K, Dugdale, RE and Lealman, G, 1989. “Rule-based ventilator management and control for neonates suffering respiratory distress” IFAC Workshop on Decision Support for Patient Management: Measurement Modelling and Control, London.Google Scholar
Zinser, K, 1988. “Design issues and knowledge representations for modern control room interfaces” In Artificial Intelligence in Real-Time Control, IFAC Workshop, Swansea, pp 123–128.Google Scholar
Zygmont, A, 1987. “Object-oriented programming and CACSD” ASEE Annual Conference,Reno,Nevada.Google Scholar