Fuzzy-Model-Based Mode Control of Complex Nonlinear Systems

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Inbunden, Engelska, 2026

Av Wenqiang Ji, Jianbin Qiu, Heting Zhang

2 019 kr

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This book presents recent theoretical findings on Sliding Mode Control (SMC) issues for various classes of complex nonlinear systems based on Takagi-Sugeno (T-S) fuzzy models. Research results and controller design methods on SMC of complex nonlinear systems through T-S fuzzy models are presented and show how the methods can be used in various practical systems, such as control of nonlinear gas absorption, water stream heating, and air-drying process in some chemical production systems.Fuzzy-Model-Based Mode Control of Complex Nonlinear Systems discusses new fuzzy SMC methods for some typical classes of complex nonlinear systems and offers new stability analysis results on sliding motion based on more advanced T-S fuzzy affine models. New convexification techniques are presented to handle the couplings in the sliding surface gain with the Lyapunov matrices and/or system matrices, and extra freedom of the existence conditions for the sliding surface gains. The book provides new SMC laws for both one-dimensional and two-dimensional systems that tend to be more complicated and widely used in many industrial processes. New types of sliding surface and dynamic sliding mode controller design methods are also covered.This book finds its audience as a reference to researchers and engineers that are engaging in the areas related to fuzzy modeling and control and SMC with its applications.

Produktinformation

Utgivningsdatum2026-04-28
Mått156 x 234 x undefined mm
FormatInbunden
SpråkEngelska
SerieEngineering Mathematics and Operations Research
Antal sidor264
FörlagTaylor & Francis Ltd
ISBN9781032694665

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Wenqiang Ji (Senior Member, IEEE) is currently a Professor at the School of Artificial Intelligence, Hebei University of Technology, Tianjin, China. Dr. Ji received a Ph.D. degree in control science and engineering from the Harbin Institute of Technology (HIT), Harbin, China, in 2019. His research interests include modeling and control of fuzzy systems, nonlinear systems, sampled-data control and filtering design, robust control, and sliding mode control. He has authored and/or coauthored more than 40 referred technical papers including many IEEE Transactions papers in the fields of Intelligent and Nonlinear Control.Jianbin Qiu (Fellow, IEEE) is currently a Full Professor at the School of Astronautics, Harbin Institute of Technology, Harbin, China. Dr. Qiu received B.Eng. and Ph.D. degrees in mechanical and electrical engineering from the University of Science and Technology of China, Hefei, China, in 2004 and 2009, respectively, and a Ph.D. degree in mechatronics engineering from the City University of Hong Kong, Hong Kong, in 2009. He was an Alexander von Humboldt Research Fellow with the Institute for Automatic Control and Complex Systems, University of Duisburg-Essen, Duisburg, Germany. Dr. Qiu His current research interests include intelligent and hybrid control systems, signal processing, and robotics and he serves as the Chairperson for the IEEE Industrial Electronics Society Harbin Chapter, China.Heting Zhang is an assistant professor at Tianjin University of Traditional Chinese Medicine, China, and her research interests include differential equations, bioinformatics, biomathematics, and their optimal control. Dr. Zhang received a BSc in Mathematics and Applied Mathematics from Heilongjiang University, China; a MS in Applied Mathematics from Harbin Institute of Technology, China; and a PhD in Mathematics from Harbin Institute of Technology, China. She is a member of the Technical Committee on Intelligent Control and Systems and serves as a reviewer for Mathematical Reviews (USA). She is currently presiding over several projects, including the National Natural Science Foundation of China, the China Postdoctoral Science Foundation, the Open Research Fund of Hubei Key Laboratory of Mathematical Sciences, and the Tianjin University of Traditional Chinese Medicine New Faculty Research Project. She is also participating in the National Science and Technology Innovation 2030, Noncommunicable Chronic Diseases-National Science and Technology Major Project.

1. Introduction. 2. State Feedback Fuzzy SMC of Continuous-Time Nonlinear Systems. 3. Output Feedback Fuzzy SMC of Continuous-Time Nonlinear Systems. 4. State Feedback Fuzzy SMC of Discrete-Time Nonlinear Systems. 5. Output Feedback Fuzzy SMC of Discrete-Time Nonlinear Systems. 6. Fuzzy Integral SMC of Nonlinear Singularly Perturbed Systems. 7. Fuzzy SMC of Continuous-Time Nonlinear Two-Dimensional Systems. 8. Fuzzy SMC of Discrete-Time Nonlinear Two-Dimensional Systems.