Jinkun, Liu Intelligent control design and MATLAB simulation. (English) Zbl 1416.93002 Singapore: Springer; Beijing: Tsinghua University Press (ISBN 978-981-10-5262-0/hbk; 978-981-13-5354-3/pbk; 978-981-10-5263-7/ebook). xv, 290 p. (2018). In a nutshell, 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 exposure of the material is structured in a logic fashion by highlighting the three pillars of intelligent control, namely fuzzy control, neural networks, and intelligent search techniques. Those are representative directions encountered in the existing literature. The book is structured into 12 chapters. The first part of the book is concerned with fuzzy control covering the main topics of expert PID control, fuzzy logic control, rule-based T-S fuzzy modeling, and adaptive fuzzy control. Included is also a chapter on the basics of fuzzy sets. Chapters 7–10 are focused on neural network control. In more detail, Chapter 7 is concerned with neural networks. Adaptive radial basis function (RBF) neural network control is covered in Chapter 8. In the sequel, adaptive sliding mode control and discrete RBF network control are presented in Chapter 9 and 10, respectively. Intelligent search techniques (Chapter 11) include commonly studied optimization tools such as genetic algorithms, differential evolution, and particle swarm optimization. Finally, Chapter 12 focuses on iterative learning control.The content of each chapter is arranged in a systematic way: the exposure of the material starts with a brief outline of the topic, followed by an algorithm (structure) of the method, and an illustrative, well-annotated code. Example results obtained for some particular parametric settings of the method are presented. The book contains a lot of illustrative material (plots and schematics).Given some conciseness of the presentation, in particular with regard to the underlying design process, to fully benefit from the material covered in the book, the reader should have some prerequisite knowledge in the discipline of intelligent control. The material on fuzzy sets is quite introductory and not well aligned with the ensuing design practices. For instance, crucial aspects of design of fuzzy sets are not discussed. References are limited and somewhat outdated.All in all, as the reference material, the book serves well its purpose: it is systematic as to the coverage of the representative topics goes.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. Reviewer: Witold Pedrycz (Edmonton) Cited in 2 Documents MSC: 93-02 Research exposition (monographs, survey articles) pertaining to systems and control theory 93C42 Fuzzy control/observation systems 93B40 Computational methods in systems theory (MSC2010) 93C40 Adaptive control/observation systems 93B12 Variable structure systems 68T05 Learning and adaptive systems in artificial intelligence Keywords:intelligent control; fuzzy control; neural networks; evolutionary methods; design; Matlab Software:Matlab PDFBibTeX XMLCite \textit{L. Jinkun}, Intelligent control design and MATLAB simulation. Singapore: Springer; Beijing: Tsinghua University Press (2018; Zbl 1416.93002) Full Text: DOI