SpringerLink Springer Engineering eBooks 2017 English+International

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Preface; Contents; 1 Introduction; References; 2 Theory and Background; 2.1 Fuzzy Inference System; 2.1.1 Type-1 Fuzzy Logic Systems; 2.1.2 Interval Type-2 Fuzzy Logic Systems; 2.2 Fuzzy Controllers; References; 3 Problem Statements; 3.1 Water Tank Controller; 3.1.1 Model Equations of the Water Tank; 3.1.2 Design of the Fuzzy Controller; 3.2 Autonomous Mobile Robot Controller; 3.2.1 General Description of Problem; 3.2.2 Fuzzy Logic Control Design; References; 4 Bee Colony Optimization Algorithm; 4.1 Proposed Method; References; 5 Simulation Results for the Proposed Methods.

5.1 Simulation Results for the Water Tank Controller5.1.1 Results for the Original Bee Colony Optimization Algorithm; 5.1.2 Results for the Fuzzy Bee Colony Optimization Algorithm for the Water Tank Controller; 5.2 Results for the Original BCO for an Autonomous Mobile Robot; 5.2.1 Results for the Fuzzy BCO for an Autonomous Mobile Robot; 6 Statistical Analysis and Comparison of Results; 7 Conclusions; Appendix; Bibliograpy; Index.

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.