Yun Li, Kiam Heong Ang, Gregory C.Y. Chong, Wenyuan Feng, Kay Chen Tan and Hiroshi Kashiwagi. CAutoCSD-Evolutionary Search and Optimisation Enabled Computer Automated Control System Design. International Journal of Automation and Computing, vol. 1, no. 1, pp. 76-88, 2004. https://doi.org/10.1007/s11633-004-0076-8
Citation: Yun Li, Kiam Heong Ang, Gregory C.Y. Chong, Wenyuan Feng, Kay Chen Tan and Hiroshi Kashiwagi. CAutoCSD-Evolutionary Search and Optimisation Enabled Computer Automated Control System Design. International Journal of Automation and Computing, vol. 1, no. 1, pp. 76-88, 2004. https://doi.org/10.1007/s11633-004-0076-8

CAutoCSD-Evolutionary Search and Optimisation Enabled Computer Automated Control System Design

doi: 10.1007/s11633-004-0076-8
  • Received Date: 2004-04-23
  • Rev Recd Date: 2004-06-23
  • Publish Date: 2004-10-01
  • This paper attempts to set a unified scene for various linear time-invariant (LTI) control system design schemes, by transforming the existing concept of computer-aided control system design (CACSD) to novel computer-automated control system design (CAutoCSD). The first step towards this goal is to accommodate, under practical constraints, various design objectives that are desirable in both time and frequency domains. Such performance-prioritised unification is aimed at relieving practising engineers from having to select a particular control scheme and from sacrificing certain performance goals resulting from pre-commitment to such schemes. With recent progress in evolutionary computing based extra-numeric, multi-criterion search and optimisation techniques, such unification of LTI control schemes becomes feasible, analytical and practical, and the resultant designs can be creative. The techniques developed are applied to, and illustrated by, three design problems. The unified approach automatically provides an integrator for zero-steady state error in velocity control of a DC motor, and meets multiple objectives in the design of an LTI controller for a non-minimum phase plant and offers a high-performance LTI controller network for a non-linear chemical process.

     

  • loading
  • [1]
    W. S. Levine(ed).[J].The Control Handbook, CRC Press/IEEE Press.1996,:-
    [2]
    Y. Li.[J].K, C. Tan, K. C. Ng, D. J. Murray-Smith, Performance based linear control system design by genetic evolution with simulated annealing, Proc. 34th IEEE CDC, New Orleans, nn. 731-73.1995,:-
    [3]
    Y. Li.[J].A. Haeussler, Artificial evolution of neural networks and its application to feedback control, Int. J. Artificial Intelligence in Engineering, vol. 10, no. 2, pp. 143-15.1996,:-
    [4]
    K. C. Ng, Switching Control Systems and Their Design Au-tomation via Genetic Algorithms, Ph.D. Thesis, Dept.of Electronics and Electrical Engineering, University of Glas-gow.1995.
    [5]
    K. C. Tan, Evolutionary Methods for Modelling and Control of Linear and Non-linear Systems, Ph.D. Thesis, Dept. of Electronics and Electrical Engineering, University of Glas-gow, mar.
    [6]
    X. Guan, K. J. MacCallum, Adopting a minimum commitment principle for computer aided geometric design systerns, Artificial Intelligence in Design, J. S. Gero,F. Sudweeks(eds), Kluwer Academic Publishers, pp.623-639,1996.
    [7]
    M. Zhuang.[J].D.P. Atherton, Automatic tuning of optimum PID controllers,IEE Proceeding-Part D, vol.140, no.1993,3:-
    [8]
    K. J.Åström, T. Hagglund, PID Controllers:Theory, Design and Tuning, Instrument Society of America,1995.
    [9]
    J. C. Doyle.[J].B. Francis, A. Tannenbaum, Feedback Control Theory, Macmillan Publishing Company, New York.1992,:-
    [10]
    M. Chowdhury.[J].Y. Li, Learning fuzzy control systems directly from the environment, Int. J. Intelligent Systems, vol. 13, no. 10-11, pp. 949-97.1998,:-
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (4595) PDF downloads(3999) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return