Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control
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Beschreibung
This book focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area. The main idea is that these two areas together can help solve various control problems and to find better results. In this book, the authors test the proposed method using five benchmark control problems. First, the water tank, temperature, mobile robot, and inverted pendulum controllers are considered. For these 4 problems, experimentation was carried out using a Type-1 fuzzy system and an Interval Type-2 system. The last control problem was the D.C. motor, for which the experiments were performed with Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. When we use fuzzy systems combined with the differential evolution algorithm, we can notice that the results obtained in each of the controllers are better and with increasing uncertainty, the results are even better. For this reason, the authors consider in this book the proposed method using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers’ behavior in complex control problems.
Focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area Demonstrates that using fuzzy systems combined with the differential evolution algorithm produces better results in each of the controllers and with increasing uncertainty, the results are even better Proposes methods using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers’ behavior in complex control problems Explains the proposed method which is tested using five benchmark control problems: the water tank, temperature, mobile robot, inverted pendulum controllers, and the D.C. motor
Autor*in
Oscar Castillo
Themen in »Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control«
Fuzzy Logic Differential Evolution Algorithm Fuzzy Controller Complex Control Type-2 Fuzzy Logic