Optimization of Type-2 Fuzzy Controllers Using the Bee Colony Algorithm (SpringerBriefs in Applied Sciences and Technology)

This book focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm and also considering the fuzzy control area. The main idea is that this areas together can to solve various control problems and to find better results. In this book we test the proposed method using two benchmark problems; the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a better stabilization, because the analysis of uncertainty is better. For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems. Preface 6 Contents 8 1 Introduction 10 References 13 2 Theory and Background 16 2.1 Fuzzy Inference System 16 2.1.1 Type-1 Fuzzy Logic Systems 16 2.1.2 Interval Type-2 Fuzzy Logic Systems 17 2.2 Fuzzy Controllers 18 References 19 3 Problem Statements 21 3.1 Water Tank Controller 21 3.1.1 Model Equations of the Water Tank 21 3.1.2 Design of the Fuzzy Controller 22 3.2 Autonomous Mobile Robot Controller 24 3.2.1 General Description of Problem 24 3.2.2 Fuzzy Logic Control Design 26 References 28 4 Bee Colony Optimization Algorithm 30 4.1 Proposed Method 35 References 38 5 Simulation Results for the Proposed Methods 40 5.1 Simulation Results for the Water Tank Controller 41 5.1.1 Results for the Original Bee Colony Optimization Algorithm 41 5.1.2 Results for the Fuzzy Bee Colony Optimization Algorithm for the Water Tank Controller 41 5.2 Results for the Original BCO for an Autonomous Mobile Robot 47 5.2.1 Results for the Fuzzy BCO for an Autonomous Mobile Robot 55 6 Statistical Analysis and Comparison of Results 62 7 Conclusions 64 Appendix 66 Bibliograpy 76 Index 77 Front Matter....Pages i-viii Introduction....Pages 1-6 Theory and Background....Pages 7-11 Problem Statements....Pages 13-21 Bee Colony Optimization Algorithm....Pages 23-32 Simulation Results for the Proposed Methods....Pages 33-54 Statistical Analysis and Comparison of Results....Pages 55-56 Conclusions....Pages 57-58 Back Matter....Pages 59-71