Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems (eBook)
XIX, 257 Seiten
Springer Singapore (Verlag)
978-981-10-0593-0 (ISBN)
This book develops a set of reference methods capable of modeling uncertainties existing in membership functions, and analyzing and synthesizing the interval type-2 fuzzy systems with desired performances. It also provides numerous simulation results for various examples, which fill certain gaps in this area of research and may serve as benchmark solutions for the readers.
Interval type-2 T-S fuzzy models provide a convenient and flexible method for analysis and synthesis of complex nonlinear systems with uncertainties.
Hongyi Li received B.S. and M.S. degrees in mathematics from Bohai University, Jinzhou, China, in 2006 and 2009, respectively, and the Ph.D. degree in intelligent control from the University of Portsmouth, Portsmouth, UK, in 2012. He is currently a Professor of the College of Engineering, Bohai University. He was a Research Associate with the Department of Mechanical Engineering, University of Hong Kong and Hong Kong Polytechnic University, from June 2010 to September 2010 and from September 2012 to December 2012, respectively.
His research interests include fuzzy control, robust control, and their applications. He is also an Associate Editor/Editorial Board member for several international journals, including Neurocomputing, Circuits, Systems, and Signal Processing, Shock and Vibration, etc.
Ligang Wu, Professor, Space Control and Inertial Technology Research Center, Harbin Institute of Technology.
Hak-Keung Lam, Professor, Department of Informatics, King's College London.
Yabin Gao, Student, Space Control and Inertial Technology Research Center, Harbin Institute of Technology.
This book develops a set of reference methods capable of modeling uncertainties existing in membership functions, and analyzing and synthesizing the interval type-2 fuzzy systems with desired performances. It also provides numerous simulation results for various examples, which fill certain gaps in this area of research and may serve as benchmark solutions for the readers. Interval type-2 T-S fuzzy models provide a convenient and flexible method for analysis and synthesis of complex nonlinear systems with uncertainties.
Hongyi Li received B.S. and M.S. degrees in mathematics from Bohai University, Jinzhou, China, in 2006 and 2009, respectively, and the Ph.D. degree in intelligent control from the University of Portsmouth, Portsmouth, UK, in 2012. He is currently a Professor of the College of Engineering, Bohai University. He was a Research Associate with the Department of Mechanical Engineering, University of Hong Kong and Hong Kong Polytechnic University, from June 2010 to September 2010 and from September 2012 to December 2012, respectively. His research interests include fuzzy control, robust control, and their applications. He is also an Associate Editor/Editorial Board member for several international journals, including Neurocomputing, Circuits, Systems, and Signal Processing, Shock and Vibration, etc.Ligang Wu, Professor, Space Control and Inertial Technology Research Center, Harbin Institute of Technology. Hak-Keung Lam, Professor, Department of Informatics, King's College London. Yabin Gao, Student, Space Control and Inertial Technology Research Center, Harbin Institute of Technology.
Introduction.- Stability and Stabilization of CTIT2FMBSs.- Output-feedback Control of CTIT2FMBSs.- Sampled-Data Control of CTIT2FMBSs.- Output Tracking Control of CTIT2FSs.- Switched Output-feedback Control of CTIT2FMBSs.- Filter Design of CTIT2FMBSs.- Fault Detection of CTIT2FMBSs.- Model Reduction of CTIT2FMBSs.- Optimal Control of DTIT2FMBSs.- State-feedback Control of DTIT2FMBSs.- Static Output-feedback Control of DTIT2FMBSs.- Guaranteed Cost Output Tracking Control of DTIT2FMBSs.
| Erscheint lt. Verlag | 29.2.2016 |
|---|---|
| Zusatzinfo | XIX, 257 p. 60 illus., 55 illus. in color. |
| Verlagsort | Singapore |
| Sprache | englisch |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Naturwissenschaften ► Physik / Astronomie ► Optik | |
| Technik ► Elektrotechnik / Energietechnik | |
| Schlagworte | fault detection • Fuzzy Control • fuzzy filtering • Interval Type-2 Fuzzy Sets • Model Reduction • optimal control • Tracking Control • TS fuzzy systems • Uncertainty |
| ISBN-10 | 981-10-0593-1 / 9811005931 |
| ISBN-13 | 978-981-10-0593-0 / 9789811005930 |
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