Intelligent Control Design and MATLAB Simulation
Description
This book offers a comprehensive introduction to intelligent control system design, using MATLAB simulation to verify typical intelligent controller designs. It also uses real-world case studies that present the results of intelligent controller implementations to illustrate the successful application of the theory. Addressing the need for systematic design approaches to intelligent control system design using neural network and fuzzy-based techniques, the book introduces the concrete design method and MATLAB simulation of intelligent control strategies; offers a catalog of implementable intelligent control design methods for engineering applications; provides advanced intelligent controller design methods and their stability analysis methods; and presents a sample simulation and Matlab program for each intelligent control algorithm.
The main topics addressed are expert control, fuzzy logic control, adaptive fuzzy control, neural network control, adaptive neural control and
intelligent optimization algorithms, providing several engineering application examples for each method.Reviews / Votes
"The book can be regarded as a handy guide to the Matlab computing environment used in the realization of a variety of commonly encountered intelligent control approaches. . The book serves well its purpose: it is systematic as to the coverage of the representative topics goes. It is logically organized. It also brings a wealth of illustrative contents (computing examples and abundant graphic illustration). The practitioners and students could appreciate all the features." (Witold Pedrycz, zbMath 1416.93002, 2019)More details
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LIU Jinkun received his BS, MS and PhD degrees from Northeastern University, Shenyang, China, in 1989, 1994 and 1997, respectively. He was a postdoctoral fellow at Zhejiang University from 1997 to 1999, and is currently a professor at Beihang University, China. He has published more than 100 research papers and eight books. His research interests include intelligent control and sliding mode control; partial differential equation (PDE) modeling and boundary control and application areas in motion control, such as flight control and robotic control, especially for under-actuated systems.