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Fuzzy Control and Identification

Book Description

This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models.

Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.

Table of Contents

  1. Cover
  2. Title page
  3. Copyright page
  4. Dedication
  5. PREFACE
  6. CHAPTER 1 INTRODUCTION
    1. 1.1 FUZZY SYSTEMS
    2. 1.2 EXPERT KNOWLEDGE
    3. 1.3 WHEN AND WHEN NOT TO USE FUZZY CONTROL
    4. 1.4 CONTROL
    5. 1.5 INTERCONNECTION OF SEVERAL SUBSYSTEMS
    6. 1.6 IDENTIFICATION AND ADAPTIVE CONTROL
    7. 1.7 SUMMARY
  7. CHAPTER 2 BASIC CONCEPTS OF FUZZY SETS
    1. 2.1 FUZZY SETS
    2. 2.2 USEFUL CONCEPTS FOR FUZZY SETS
    3. 2.3 SOME SET-THEORETIC AND LOGICAL OPERATIONS ON FUZZY SETS
    4. 2.4 EXAMPLE
    5. 2.5 SINGLETON FUZZY SETS
    6. 2.6 SUMMARY
  8. CHAPTER 3 MAMDANI FUZZY SYSTEMS
    1. 3.1 IF-THEN RULES AND RULE BASE
    2. 3.2 FUZZY SYSTEMS
    3. 3.3 FUZZIFICATION
    4. 3.4 INFERENCE
    5. 3.5 DEFUZZIFICATION
    6. 3.6 EXAMPLE: FUZZY SYSTEM FOR WIND CHILL
    7. 3.7 SUMMARY
  9. CHAPTER 4 FUZZY CONTROL WITH MAMDANI SYSTEMS
    1. 4.1 TRACKING CONTROL WITH A MAMDANI FUZZY CASCADE COMPENSATOR
    2. 4.2 TUNING FOR IMPROVED PERFORMANCE BY ADJUSTING SCALING GAINS
    3. 4.3 EFFECT OF INPUT MEMBERSHIP FUNCTION SHAPES
    4. 4.4 CONVERSION OF PID CONTROLLERS INTO FUZZY CONTROLLERS
    5. 4.5 INCREMENTAL FUZZY CONTROL
    6. 4.6 SUMMARY
  10. CHAPTER 5 MODELING AND CONTROL METHODS USEFUL FOR FUZZY CONTROL
    1. 5.1 CONTINUOUS-TIME MODEL FORMS
    2. 5.2 MODEL FORMS FOR DISCRETE-TIME SYSTEMS
    3. 5.3 SOME CONVENTIONAL CONTROL METHODS USEFUL IN FUZZY CONTROL
    4. 5.4 SUMMARY
  11. CHAPTER 6 TAKAGI—SUGENO FUZZY SYSTEMS
    1. 6.1 TAKAGI–SUGENO FUZZY SYSTEMS AS INTERPOLATORS BETWEEN MEMORYLESS FUNCTIONS
    2. 6.2 TAKAGI–SUGENO FUZZY SYSTEMS AS INTERPOLATORS BETWEEN CONTINUOUS-TIME LINEAR STATE-SPACE DYNAMIC SYSTEMS
    3. 6.3 TAKAGI–SUGENO FUZZY SYSTEMS AS INTERPOLATORS BETWEEN DISCRETE-TIME LINEAR STATE-SPACE DYNAMIC SYSTEMS
    4. 6.4 TAKAGI–SUGENO FUZZY SYSTEMS AS INTERPOLATORS BETWEEN DISCRETE-TIME DYNAMIC SYSTEMS DESCRIBED BY INPUT–OUTPUT DIFFERENCE EQUATIONS
    5. 6.5 SUMMARY
  12. CHAPTER 7 PARALLEL DISTRIBUTED CONTROL WITH TAKAGI—SUGENO FUZZY SYSTEMS
    1. 7.1 CONTINUOUS-TIME SYSTEMS
    2. 7.2 DISCRETE-TIME SYSTEMS
    3. 7.3 PARALLEL DISTRIBUTED TRACKING CONTROL
    4. 7.4 PARALLEL DISTRIBUTED MODEL REFERENCE CONTROL
    5. 7.5 SUMMARY
  13. CHAPTER 8 ESTIMATION OF STATIC NONLINEAR FUNCTIONS FROM DATA
    1. 8.1 LEAST-SQUARES ESTIMATION
    2. 8.2 BATCH LEAST-SQUARES FUZZY ESTIMATION IN MAMDANI FORM
    3. 8.3 RECURSIVE LEAST-SQUARES FUZZY ESTIMATION IN MAMDANI FORM
    4. 8.4 LEAST-SQUARES FUZZY ESTIMATION IN TAKAGI–SUGENO FORM
    5. 8.5 GRADIENT FUZZY ESTIMATION IN MAMDANI FORM
    6. 8.6 GRADIENT FUZZY ESTIMATION IN TAKAGI–SUGENO FORM
    7. 8.7 SUMMARY
  14. CHAPTER 9 MODELING OF DYNAMIC PLANTS AS FUZZY SYSTEMS
    1. 9.1 MODELING KNOWN PLANTS AS T–S FUZZY SYSTEMS
    2. 9.2 IDENTIFICATION IN INPUT–OUTPUT DIFFERENCE EQUATION FORM
    3. 9.3 IDENTIFICATION IN COMPANION FORM
    4. 9.4 SUMMARY
  15. CHAPTER 10 ADAPTIVE FUZZY CONTROL
    1. 10.1 DIRECT ADAPTIVE FUZZY TRACKING CONTROL
    2. 10.2 DIRECT ADAPTIVE FUZZY MODEL REFERENCE CONTROL
    3. 10.3 INDIRECT ADAPTIVE FUZZY TRACKING CONTROL
    4. 10.4 INDIRECT ADAPTIVE FUZZY MODEL REFERENCE CONTROL
    5. 10.5 ADAPTIVE FEEDBACK LINEARIZATION CONTROL
    6. 10.6 SUMMARY
  16. REFERENCES
  17. APPENDIX COMPUTER PROGRAMS
  18. Index