Analysis and design for a class of complex control systems .1. Fuzzy modelling and identification

被引:271
作者
Cao, SG [1 ]
Rees, NW [1 ]
Feng, G [1 ]
机构
[1] UNIV NEW S WALES,SCH ELECT ENGN,DEPT SYST & CONTROL,SYDNEY,NSW 2052,AUSTRALIA
关键词
complex systems; fuzzy control; fuzzy models; identification; modelling;
D O I
10.1016/S0005-1098(97)00010-1
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper is the first of two dealing with the analysis and design of a class of complex control systems. This part deals with fuzzy modelling and identification. The second paper is concerned with fuzzy controller design. We believe that these two papers show a way to analyze and design complex control systems using a combination of fuzzy logic and modern control theory. The complex systems studied in these two papers can be represented by a fuzzy aggregation of a set of local linear models. The identification can be divided into two procedures. The first procedure is the identification of the membership functions, including the determination of the number of fuzzy rules, and the estimation of the parameters in the membership functions. The second is the identification of the local linear models, including the determination of the structure and the parameters of the local rule maps and the global rule interpolation. Two examples are used to demonstrate the application of the modelling method. (C) 1997 Elsevier Science Ltd.
引用
收藏
页码:1017 / 1028
页数:12
相关论文
共 14 条
  • [1] [Anonymous], LECT NOTES CONTROL I
  • [2] IDENTIFICATION OF DYNAMIC FUZZY MODELS
    CAO, SG
    REES, NW
    [J]. FUZZY SETS AND SYSTEMS, 1995, 74 (03) : 307 - 320
  • [3] HILHORST RA, 1994, AUTOMATICA, V30, P319
  • [4] APPLICATION OF FUZZY ALGORITHMS FOR CONTROL OF SIMPLE DYNAMIC PLANT
    MAMDANI, EH
    [J]. PROCEEDINGS OF THE INSTITUTION OF ELECTRICAL ENGINEERS-LONDON, 1974, 121 (12): : 1585 - 1588
  • [5] A REVIEW AND COMPARISON OF 6 REASONING METHODS
    NAKANISHI, H
    TURKSEN, IB
    SUGENO, M
    [J]. FUZZY SETS AND SYSTEMS, 1993, 57 (03) : 257 - 294
  • [6] NUJMEIJER H, 1990, NONLINEAR DYNAMICAL
  • [7] PALIZBAN HA, 1995, P IFAC S CONTR POW P, P177
  • [8] NEUROCONTROL OF NONLINEAR DYNAMICAL-SYSTEMS WITH KALMAN FILTER TRAINED RECURRENT NETWORKS
    PUSKORIUS, GV
    FELDKAMP, LA
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1994, 5 (02): : 279 - 297
  • [9] Fuzzy-logic-based approach to qualitative modeling
    Sugeno, Michio
    Yasukawa, Takahiro
    [J]. IEEE Transactions on Fuzzy Systems, 1993, 1 (01) : 7 - 31
  • [10] FUZZY IDENTIFICATION OF SYSTEMS AND ITS APPLICATIONS TO MODELING AND CONTROL
    TAKAGI, T
    SUGENO, M
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1985, 15 (01): : 116 - 132