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Autorenporträt
Dr. Qikun Shen received the B.Sc. degree in computer science and applications from the Chinese University of Mining and Technology, Xuzhou, China, in 1996, the M.Sc. degree in computer science and applications from Yangzhou University, Yangzhou, China, in 2007, and the Ph.D. degree in control theorem and control applications from the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2015.
Dr. Shen is currently Professor with the College of Information Engineering, Yangzhou University. His current research interests include distributed control, consensus control, fault-tolerant control, adaptive control, fuzzy control, neural networks-based control, and intelligent control.
Inhaltsangabe
Introduction.- Adaptive Observer Based Tracking Control and Fault Detection with Known Higher Input Powers.- Fuzzy Adaptive Fault Tolerant Backstepping Supervisory Control for Uncertain Systems with Known Higher Input Powers.- Stability Control, Fault Detection and Estimation with Unknown System Input Power.- Adaptive Fault Tolerant Output Tracking Backstepping Control with Unknown Higher Input Powers.- Robust Fault-Tolerant Adaptive Tracking Control with Unknown System Input Powers and Dynamic Disturbances.- Adaptive Neural Distributed Fault Tolerant Consensus with Unmodeled Dynamics and Unknown Higher Input Power.- Distributed Fuzzy FTC for 2D Nonlinear Mass with Unknown Input Powers.- Conclusion and Future Research Directions.
Introduction.- Adaptive Observer Based Tracking Control and Fault Detection with Known Higher Input Powers.- Fuzzy Adaptive Fault Tolerant Backstepping Supervisory Control for Uncertain Systems with Known Higher Input Powers.- Stability Control, Fault Detection and Estimation with Unknown System Input Power.- Adaptive Fault Tolerant Output Tracking Backstepping Control with Unknown Higher Input Powers.- Robust Fault-Tolerant Adaptive Tracking Control with Unknown System Input Powers and Dynamic Disturbances.- Adaptive Neural Distributed Fault Tolerant Consensus with Unmodeled Dynamics and Unknown Higher Input Power.- Distributed Fuzzy FTC for 2D Nonlinear Mass with Unknown Input Powers.- Conclusion and Future Research Directions.
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