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Installieren Sie die genialokal App auf Ihrem Startbildschirm für einen schnellen Zugriff und eine komfortable Nutzung.
Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and ou
Zhongsheng Hou received his bachelor's and master's degrees from Jilin University of Technology, Changchun, China, in 1983 and 1988, and his PhD from Northeastern University, Shenyang, China, in 1994. In 1997, he joined Beijing Jiaotong University, Beijing, China, and is currently a full professor and the founding director of the Advanced Control Systems Lab, and the dean of the Department of Automatic Control. His research interests are in the fields of data-driven control, model-free adaptive control, iterative learning control, and intelligent transportation systems. He has over 110 peer-reviewed journal papers published and over 120 papers in prestigious conference proceedings. His personal website is available at acsl.bjtu.edu.cn. Shangtai Jin received his BS, MS, and PhD degrees from Beijing Jiaotong University, Beijing, China, in 1999, 2004, and 2009, respectively. He is currently a lecturer with Beijing Jiaotong University. His research interests include model-free adaptive control, iterative learning control, and intelligent transportation systems.
Introduction. Recursive Parameter Estimation for Discrete-Time Systems. Dynamic Linearization Approach of Discrete-Time Nonlinear Systems. Model-Free Adaptive Control of SISO Discrete-Time Nonlinear Systems. Model-Free Adaptive Control of MIMO Discrete-Time Nonlinear Systems. Model-Free Adaptive Predictive Control. Model-Free Adaptive Iterative Learning Control. Model-Free Adaptive Control for Complex Connected Systems and Modularized Controller Design. Robustness of Model-Free Adaptive Control. Symmetric Similarity for Control System Design. Applications. Conclusions and Perspectives. References. Index.
