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      Non-monotonic Approach to Robust H? Control of Multi-model Systems

      AvJiwei Wen,Alireza Nasiri

      Häftad, Engelska, 2019

      Del i serien Emerging Methodologies and Applications in Modelling, Identification and Control

      1 178 kr

      Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

      Beskrivning

      Non-monotonic Approach to Robust H? Control of Multi-model Systems focuses on robust analysis and synthesis problems for multi-model systems based on the non-monotonic Lyapunov Functionals (LFs) approach that enlarges the stability region and improves control performance. By fully considering the diversity of switching laws, the multi-step time difference, the multi-step prediction, and the expansion of system dimension, the non-monotonic LF can be properly constructed. The focus of this book is placed on the H? state feedback control, H? filtering and H? output feedback control for multi-model systems via a non-monotonic LF approach.

      The book's authors provide illustrative examples to show the feasibility and efficiency of the proposed methods, along with practical examples that demonstrate the effectiveness and potential of theoretical results.



      • Offers tools for the analysis and design of control processes where the process can be represented by multi-models
      • Presents a comprehensive explanation of recent developments in non-monotonic approaches to robust H-infinity control of multi-model systems
      • Gives numerical examples and simulation results in each chapter to demonstrate engineering potential

      Produktinformation

      • Utgivningsdatum:2019-06-07
      • Mått:152 x 229 x 14 mm
      • Vikt:360 g
      • Format:Häftad
      • Språk:Engelska
      • Serie:Emerging Methodologies and Applications in Modelling, Identification and Control
      • Antal sidor:222
      • Förlag:Elsevier Science
      • ISBN:9780128148686

      Utforska kategorier

      • Elektronik och kommunikationer inom Naturvetenskap och teknik

      Mer om författaren

      Jiwei Wen received his Ph.D. degree in Control Science and Control Engineering from Jiangnan University, Wuxi, China, in 2011. From 2015 to 2016, he was a visiting scholar with the Department of Electrical and Computer Engineering, University of Auckland. Currently, he is an associate professor of School of Internet of Things Engineering, Jiangnan University, Wuxi, China. He is also a researcher in the Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Wuxi, China. His research interests include non-monotonic filtering and control approach, stochastic switched system, model predictive control and T-S fuzzy modelling and control. He has/had served as reviewer of a number of international journals. He is an Associate Editor of the International Journal of Sensors, Wireless Communications and Control. Alireza Nasiri holds a PhD degree from the University of Auckland, New Zealand. He is currently Assistant Professor in the Department of Electrical and Computer Engineering at Hormozgan University and vice president of Hormozgan Science and Technology Park, Iran. He received his B.Sc. and M.Sc. degrees in electrical engineering from the University of Tehran and Iran University of Science and Technology, respectively. His research interests are nonlinear control, fuzzy control, H∞ control, active noise control and fault tolerant control. Sing Kiong Nguang is a professor with the Department of Electrical and Computer Engineering at the University of Auckland, Auckland, New Zealand. He received the B.E. (with first class honors) and the Ph.D. degree from the Department of Electrical and Computer Engineering at the University of Newcastle, Callaghan, Australia, in 1992 and 1995, respectively. He has published over 300 refereed journal and conference papers on nonlinear control design, nonlinear control systems, nonlinear time delay systems, nonlinear sampled-data systems, networked control systems, biomedical systems modelling, fuzzy modeling and control, biological systems modelling and control, and food and bio-product processing. He has/had served on the editorial board of a number of international journals. He is the Chief-Editor of the International Journal of Sensors, Wireless Communications and Control. Dhafer J. Almakhles received the B.E. degree from the department of Electrical Engineering of King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, in 2006 and the Master’s (Hons.) degree from the University of Auckland, Auckland, New Zealand, in 2011. He completed his Ph.D. degree in 2016 from the University of Auckland. During his PhD, he managed to publish and submit high quality journal and conference papers and one book chapter. Currently, he is Assistant Professor at the Department of Communication and Networks Engineering and the coordinator of renewable energy research unit, Prince Sultan University, Riyadh, Saudi Arabia. His research interests include networked, event-triggered and quantized control systems, nonlinear control system, sliding mode control and real-time implementations on FPGA.

      Innehållsförteckning

      • 1. Introduction2. Robust H- State Feedback Controller design of discrete-time T-S Fuzzy Systems: A Non-monotonic Approach3. Robust H- Filtering of T-S Fuzzy Systems: A Non-monotonic Approach4. Robust H- Output Feedback Control for T-S Fuzzy Systems: A Non-monotonic Approach5. H- State feedback Control of Discrete-time Switched Systems via One-step ahead Lyapunov Function Approach6. Stability, l2-Gain and Robust H- Control of Switched Systems via Multi-step ahead Non-monotonic Approach7. H- filtering for Discrete-time Switched Systems via Multi-step ahead Non-monotonic Approach8. H- Output feedback Control of Discrete-time Switched Systems via Multi-step ahead Non-monotonic Approach9. Robust H- state feedback Control of Discrete-time Non-homogenous Markovian Jump Systems via Multi-step Lyapunov Function Approach10. Robust H- filtering of Discrete-time Non-homogenous Markovian Jump Systems via Multi-step Lyapunov Function Approach11. Conclusions
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