Fuzzy Decision Making in Modeling and Control (World Scientific Series in Robotics and Intelligent Systems) 9810248776, 9789810248772

Table of contents :
Contents......Page 14
Foreword......Page 8
Preface......Page 10
Acknowledgments......Page 12
1.1 Control systems......Page 21
1.2 Advanced control systems......Page 24
1.3 Fuzzy control and decision making......Page 27
1.4 Chapter outline......Page 33
2. Fuzzy Decision Making......Page 37
2.1 Classification of decision making methods......Page 38
2.2 General formulation of decision making......Page 40
2.3 Fuzzy decisions......Page 43
2.4 Fuzzy multiattribute decision making......Page 47
2.5 Summary and concluding remarks......Page 56
3.1 Main types of aggregation......Page 57
3.2 Triangular norms and conorms......Page 60
3.3 Averaging and compensatory operators......Page 63
3.4 Generalized operators......Page 73
3.5 Weighted aggregation......Page 77
3.6 Summary and concluding remarks......Page 83
4.1 Decision making and control......Page 85
4.2 Conventional fuzzy controllers......Page 87
4.3 Nonlinear controllers using decision functions......Page 94
4.4 Examples of fuzzy aggregated membership control......Page 107
4.5 Summary and concluding remarks......Page 111
5.Modeling and Identification......Page 113
5.1 Formulation of the modeling problem......Page 114
5.2 Fuzzy modeling......Page 116
5.3 Fuzzy identification......Page 121
5.4 Identification by product-space fuzzy clustering......Page 123
5.5 Summary and concluding remarks......Page 128
6.Fuzzy Decision Making for Modeling......Page 129
6.1 Fuzzy decisions in fuzzy modeling......Page 130
6.2 Defuzzification as a fuzzy decision......Page 145
6.3 Application example: fuzzy security assessment......Page 150
6.4 Summary and concluding remarks......Page 154
7.Fuzzy Model-Based Control......Page 157
7.1 Inversion of fuzzy models......Page 158
7.2 Inversion of a singleton fuzzy model......Page 163
7.3 Inversion of an affine Takagi-Sugeno fuzzy model......Page 171
7.4 On-line adaptation of feedforward fuzzy models......Page 175
7.5 Predictive control using the inversion of a fuzzy model......Page 177
7.6 Pressure control of a fermentation tank......Page 179
7.7 Fuzzy compensation of steady-state errors......Page 188
7.8 Summary and concluding remarks......Page 194
8. Performance Criteria......Page 197
8.1 Design specifications......Page 198
8.2 Classical performance specifications......Page 202
8.3 Classical performance criteria......Page 206
8.4 Fuzzy performance criteria......Page 210
8.5 Summary and concluding remarks......Page 212
9. Model-Based Control with Fuzzy Decision Functions......Page 215
9.1 Fuzzy decision making in predictive control......Page 216
9.2 Fuzzy model-based predictive control......Page 219
9.3 Fuzzy criteria for decision making in control......Page 225
9.4 Application examples......Page 232
9.5 Design of decision functions from expert knowledge......Page 243
9.6 Summary and concluding remarks......Page 249
10. Derivative-Free Optimization......Page 251
10.1 Branch-and-bound optimization for predictive control......Page 252
10.2 Branch-and-bound optimization for fuzzy predictive control......Page 260
10.3 Application example for fuzzy branch-and-bound......Page 264
10.4 Genetic algorithms for optimization in predictive control......Page 266
10.5 Application example with genetic algorithms......Page 278
10.6 Summary and concluding remarks......Page 281
11. Advanced Optimization Issues......Page 283
11.1 Convex optimization in fuzzy predictive control......Page 284
11.2 Application example with convex fuzzy optimization......Page 288
11.3 Fuzzy predictive filters......Page 290
11.4 Application example for fuzzy predictive filters......Page 294
11.5 Summary and concluding remarks......Page 297
12. Application Example......Page 301
12.1 Air-conditioning systems......Page 302
12.2 Fan-coil systems......Page 303
12.3 Fuzzy models of the air-conditioning system......Page 305
12.4 Controllers applied to the air-conditioning system......Page 309
12.5 Summary and concluding remarks......Page 319
13.1 Theoretical analysis of FAME controllers......Page 321
13.4 Control with approximate models......Page 322
13.7 B&B for MIMO systems......Page 324
Appendix A Model-Based Predictive Control......Page 327
A.1.2 Objective function......Page 328
A.1.4 Receding horizon principle......Page 330
A.2 Modeling in MBPC......Page 331
A.3 Optimization problems......Page 332
A.4 Compensation of model-plant mismatch and disturbances......Page 333
B.l Classical internal model control......Page 335
B.2 MBPC in an internal model control scheme......Page 337
Bibliography......Page 339
Index......Page 351