02873nam 2200493 450 991048486820332120210406130732.03-030-62133-210.1007/978-3-030-62133-9(CKB)4100000011585997(MiAaPQ)EBC6403596(DE-He213)978-3-030-62133-9(PPN)252508378(EXLCZ)99410000001158599720210406d2021 uy 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierDifferential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control /Oscar Castillo, Patricia Ochoa, Jose Soria1st ed. 2021.Cham, Switzerland :Springer,[2021]©20211 online resource (VII, 61 p. 47 illus., 42 illus. in color.) SpringerBriefs in applied sciences and technology. Computational intelligence3-030-62132-4 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.SpringerBriefs in applied sciences and technology.Computational intelligence.Fuzzy logicEvolution equationsFuzzy logic.Evolution equations.511.3Castillo Oscar762265Ochoa PatriciaSoria JoséMiAaPQMiAaPQMiAaPQBOOK9910484868203321Differential evolution algorithm with type-2 fuzzy logic for dynamic parameter adaptation with application to intelligent control2846066UNINA