文件名称:
Fuzzy Control Systems
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上传时间: 2008-10-06
详细说明： Foreword Author's Biographical Information Part A—General Theory Chapter 1—Learning Algorithms for Neuro-Fuzzy Networks 1 Introduction 2 Neuro-Fuzzy Networks 2.1 The Conventional Fuzzy Model 2.2 From Fuzzy to Neuro-Fuzzy 2.3 Initialization 2.4 Training Procedure 3 Weight identification for Φ2 3.1 Gradient Descent 3.2 Least Square Method 3.3 Recursive Le ast Square Method 4 Optimisation of Membership Functions 4.1 First Order Approximation of Gradient 4.2 Random Optimization 5 Examples 5.1 Non Differentiable NFN 5.2 Differentiable NFN 6 Conclusion References Chapter 2—Towards a Unified Theory of Intelligent Autonomous Control Systems 1 Introduction 2 State of the Art and Future Challenges 2.1 Three views of what are the most important robotic issues 2.2 Some Pros and Cons of the Available Methodologies 3 Adaptive Systems and the Dual Control Problem 3.1 Identification vs. Optimization in Changing Environments 4 A Systemic Approach to Behavioural Specification of Intelligent Systems 4.1 A Conceptual Framework for Describing and Synthesizing Actions of an Intelligent System 5 Behavioural Specification of the Activities of a System of Interacting Actors 5.1 Models of Actors interacting with their Environments 6 Fuzzification of Formal Models of Adaptive Autonomous Control Systems 6.1 The Effects of Imprecision and Uncertainty 6.2 Fuzzification of Power Sets and Relational Systems 7 Fuzzy identification 8 Introducing Control Hierarchies 8.1 The Behaviour of an ‘Intelligent’ Autonomous System 8.2 From Two-level to Multi-level Control 8.3 Organization and Strategies of Multi-Level Control 9 From Abstract Logic Designs to Technological Realizations 9.1 Generalised Virtual Machines 9.2 A Reconfigurable Architectural Shell with General Knowledge Structures References Chapter 3—Reasoning by Analogy in Fuzzy Controllers 1 Introduction 2 Problem Statement 3 Logic-Based Neurons 4 Analogical Processor - Architecture 5 Learning in the AP 6 Reasoning by Analogy in the AP Structure 7 Analogical Reasoning in Presence of Input Uncertainty 7 Characteristics of the Reasoning Scheme 8 Conclusions References Appendix A Chapter 4—Information Complexity and Fuzzy Control 1 Preamble 2 Introduction 3 Uncertainty of Membership Functions 3.1 Motivation 3.2 Information of crisp assignments 3.3 Information of fuzzy sets 4 Comparison of Uncertainties 4.1 Maximum uncertainty operations 4.2 Minimization of uncertainty 5 Closing Remarks References Chapter 5—Alternative Structures for Knowledge Representation in Fuzzy Logic Controllers 1 Introduction 2 Basic Structures of Fuzzy Logic Controller 3 Certainty Qualified Antecedents 4 Alternative Formulations for Rule Outputs 5 Chaining of Fuzzy Rules 6 Decoupled Inputs 7 Hierarchical Representation of Rules 8 Conclusion References Part B—Methodologies and Algorithms Chapter 6—Dynamic Analysis of Fuzzy Logic Control Structures 1 Introduction 2 Fuzzy Control Structures 3 Dynamic Analysis and Design 4 Fuzzy Controllers with Consequent Functions 5 Example 6 Conclusions References Chapter 7—Intelligent Fuzzy Controller for Event-Driven, Real Time Systems and its VLSI Implementation 1 Fuzzy Logic Finite State Machine 2 Algorithm of Creating a Multiple-Input Fuzzy Model 3 Hardware Accelerator 4 VLSI Implementation 5 Conclusions References Chapter 8—Constraint-Oriented Fuzzy Control Schemes for Cart-Pole Systems by Goal Decoupling and Genetic Algorithms 1 Introduction 2 The Notion of Constraint-Oriented Fuzzy Control 3 Construction of Fuzzy Control Scheme by Decoupling the Goals on Cart and Pole 4 Construction of Fuzzy Control Systems by Genetic Algorithm Techniques 5 Construction of Control Scheme for Cart-Pole Systems by Genetic Algorithms 6 Conclusions References Chapter 9—A Self Generating and Tuning Method for Fuzzy Modeling using Interior Penalty Method and its Application to Knowledge Acquisition of Fuzzy Controller 1 Introduction 2 Self Tuning Method Using Interior Penalty Method 2.1 Problem Formulation 2.2 Self Tuning Method Using Interior Penalty Method 2.3 Numerical Example 3 Hybrid Algorithm for Rule Generation and Parameter tuning 3.1 Rule Generation Method 3.2 Hybrid Algorithm for Rule Generation and Parameter Tuning 3.3 Advantage of the Hybrid Method Over Similar Methods 3.4 Numerical Examples 4 Application to Knowledge Acquisition of Fuzzy Controller 5 Conclusion References Chapter 10—Fuzzy Control of VSS Type and its Robustness 1 Introduction 2 Fuzzy Control of VSS Type 2.1 VSS Controller 2.2 Fuzzy VSS Controller 3 Rule Generation of Fuzzy Controller 4 Parameter Adjustment of Fuzzy Controller 4.1 Rule Generation of Fuzzy Controller 4.2 Adjustment of Membership Functions 5 Robustness of Fuzzy Controller 6 Conclusions References Chapter 11—The Composition of Heterogeneous Control Laws 1 Introduction 2 Qualitative Descriptions of Incomplete Knowledge 2.1 The Fuzzy-Set Representation 2.2 Landmark-Based Representation 3 A Hetrogeneous Controller for the Water Tank 3.1 The Water Tank 3.2 Overlapping Operating Regions 3.3 Heterogeneous Control Laws 4 Guarantees 4.1 Qualitative Combination of Local Properties 4.2 Qualitative Analysis of the Global Control Law 5 Simulation Results 6 Integral Action 7 Relationship to Fuzzy Logic Control References Chapter 12—Synthesis of Nonlinear Controllers via Fuzzy Logic 1 Introduction 2 Fuzzy Control Systems 2.1 Control Computation 3 Problem Statement 3.1 Assumptions and Definitions 3.2 Formulation of the control law 4 Discussion 5 Conclusion Reference Chapter 13—Fuzzy Controls under Product-Sum-Gravity Methods and New Fuzzy Control Methods 1 Introduction 2 Min-Max-Gravity Method 3 Point at Issue of Min-Max-Gravity Method 4 Product-Sum-Gravity Method 5 Comparison of Min-Max-Gravity Method and Product-Sum-Gravity Method 6 Realization of PID Controllers by Product-Sum-Gravity Method 7 Fuzzy Control Results 8 New Fuzzy Reasoning Methods and Control Results 9 Conclusion References Chapter 14—Fuzzy Modeling for Adaptive Process Control 1 Introduction 2 Modeling Methodology 3 Preliminaries 4 Modeling Strategy 5 Hyperellipsoidal Clustering 5.1 Criterion 5.2 Algorithm 5.3 Design Parameters 5.4 Membership Functions 6 Consequence Modeling 6.1 Linear Substructures 6.2 Modeling Support 7 Premise Modeling 7.1 Conditional Variables 7.2 Model Evaluation 8 Fuzzy Dynamic Model 9 Predictive Control 10 Conclusion References Chapter 15—Fuzzy Controller with Matrix Representation 1 Introduction 2 Fuzzy Control Statements 3 Basic Concept of Matrix Representation 4 Reduction of Matrix Representation 5 Reduction by Simple Self-Tuning 6 Self-Tuning by Modified Simplex Method 7 Neural Networks for Fuzzy Controller 7.1 Neural Network 7.2 Heuristic Algorithm 7.3 Application to Traffic Control 8 Conclusion References Chapter 16—A Self-Tuning Method of Fuzzy Reasoning by Genetic Algorithm 1 Introduction 2 A Conventional Self-Tuning Method 2.1 Learning Algorithm Using Descent Method 2.2 Problems of Conventional Self-Tuning Method 3 Optimization of the Inference Rules by Genetic Algorithm 3.1 Genetic Algorithm 3.2 A Learning Procedure of GA 3.3 Algorithm to Optimize Inference Rules 3.4 Self-Tuning Procedure 4 Numerical Examples 5 Conclusion References Chapter 17—Hybrid Neural-Fuzzy Reasoning Model with Application to Fuzzy Control 1 Introduction 2 Fuzzy Models 2.1 Fuzzy Reasoning Method 2.2 New Fuzzy Reasoning Method 3 Hybrid Neural-Fuzzy Reasoning Model 3.1 HNFRM Design 3.2 HNFRM Control of DC Motor 4 Conclusions References Chapter 18—Learning Fuzzy Control Rules from Examples 1 Introduction 2 The SC-Net Approach 2.1 Dynamic Plateau Modification of Fuzzy Membership Functions 3 Learning Fuzzy Motor Control 3.1 Description of Problem 3.2 Description of Experiments 4 Summary References Chapter 19—A Computational Approach to Fuzzy Logic Controller Design and Analysis Using Cell State Space Methods 1 Introduction 2 Control Problem 2.1 Set Point Control 2.2 Optimal Control 3 Cell State Space Optimal Control 3.1 Cell-to-Cell Mapping 3.2 The Unraveling Algorithm 3.3 Nonuniform Quantization 3.4 Optimal Control Algorithm 4 Fuzzy Logic Controller Tuning 4.1 Fuzzy Logic Controller Format 4.2 Parameter Identification 4.3 Stability and Performance Analysis of the Closed-Loop FLC System 5 Angular-Position Control of an Inverted Pendulum 5.1 Design Procedure 5.2 FLC Scaling and Adaptation 6 Extensions to Three and Four Variables 6.1 Effects of Cell Mapping Errors in Three and Four Dimensions 6.2 The Mapping Error Cost Function 6.3 Cascading 6.4 Map Resolution Enhancement 7 Summary and Conclusions References Chapter 20—An Adaptive Fuzzy Control Model Based on Fuzzy Neural Networks 0 Introduction 1 Building a Fuzzy Control System 1.1 The Definitions of Layers 1.2 The Definitions of Weights 1.3 The Definitions of Transfer Functions and Implementation of FCNN 1.4 The Learning Rules and Learning Capacity of the FCNN 1.4.1 Logic Neural Networks 1.4.2 Learning of Membership Function 1.4.3 Learning of FCNN 1.5 Factor Analysis According to the Learning Results of FCNN 2 The Implementation of Fuzzy Control 3 Controllability and Stability of Fuzzy Control 4 The Comparisons Between the Fuzzy Control Theory and Modern Control Theory Conclusion References Part C—Implementations and Applications Chapter 21—Human Friendly Fuzzy Transportation System 1 Introduction 2 System Configuration 3 Fuzzy Language Understanding and Fuzzy Image Recognition 3.1 Learning of Work as Language Model 3.2 Work Identification by Oral Command 4 Fuzzy Path Planning 4.1 Traveling Route Planning Technique 4.2 Results 4.3 Future Subjects References Chapter 22—Control of a Chaotic System using Fuzzy Logic 1 Introduction 2 The Chaotic System 3 Surface-Fitting and the Analytical Solution 4 Genetic Algorithm-Designed Fuzzy Logic Controller 4.1 The Fuzzy Logic Controller 4.2 Tuning The Fuzzy Logic Controller With A Genetic Algorithm 5 Results 6 Summary References Chapter 23—Applications of a Fuzzy Control Technique to Superconducting Actuators using High-Tc Superconductors 1 Introduction 2 Superconducting Levitation Mechanism 3 Superconducting Radial Bearing 4 Superconducting Linear Actuator 5 Superconducting Pump Actuator 6 Conclusions References Chapter 24—A Fuzzy Logic Based Approach to Machine-Tool Control Optimization 1 Introduction 2 Position Control 3 Direct Rule-Based Fuzzy Controller 3.1 Metarules 4 Self-Organizing Fuzzy Controller 4.1 Performance Table 4.2 Algorithm to Modify Rules 5 The SPB System 5.1 Hardware 5.2 Software 5.3 Performance Indices 6 Results Resume 7 Fuzzy Position Control of Machine-Tools: Conclusions 8 A More General Approach: Towards the Concept of Intelligent Machining References Chapter 25—Fuzzy Management of Cache Memories 1 Introduction 2 Organization of Cache Memory 3 Fuzzy Cache Management 4 Simulation Results 5 Conclusion References Chapter 26—Fuzzy Controllers on Semi-Custom VLSI Chips 1 Introduction 2 Logic Synthesis of Fuzzy Controllers 2.1 Single-input Single-output Fuzzy Controllers 2.2 Numerical Example 2.2 Multi-input Single-output Fuzzy Controllers 3 FPGA Implementation 4 Conclusions References Chapter 27—General Analysis of Fuzzy-Controlled Phase-Locked Loop 1 Introduction 2 Possibilities of Fuzzy Control in PLLS 2.1 Control Of The Loop Gain 2.2 Control Of The Phase Comparator 3 PLL Parameters and Adaptability 4 The Case of Synchronous and Coherent Phase-Locked Synchronous Oscillators 5 Performance Analysis of an Analog, Fuzzy-Controlled PLL 6 The Stability of F-PLL and Chaotic F-PLL 7 Advantages and Limits of F-PLL References Chapter 28—A Fuzzy Logic Controller for a Rigid Disk Drive 1 Introduction 2 Seek Control Method 2.1 Seek Control Method Of RDD 2.2 Open-loop, Bang-bang Seek Control Method 3 Seek Employing Fuzzy Logic 4 Trial Seek Employing Fuzzy Logic 4.1 Simulation 4.2 Trial seek 4.3 Experimental results 5 Seek Table Reference 5.1 Correcting For Actuator Coil Resistance Due To Temperature Change [2] 5.2 Results Of Correction For Coil Resistance 6 Revised Seek Table Reference [3] 6.1 Acceleration Time Reference Method Employing Quasi-Fuzzy Inference 6.2 Temperature Correction Method For Coil Resistance Variation 6.3 Experimental Results 7 Correcting Force Unevenness 7.1 Results Of Force Unevenness Correction 8 Conclusion Acknowledgement References Index Copyright © CRC Press LLC ...展开收缩
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