Springer Event-Triggered Active Disturbance Rejection Control: Theory and Applications: 356 (Studies in Systems, Decision and Control, 356)

The past few years have seen the attention and rapid developments in event-triggered sampled-data systems, in which the effect of event-triggered sensor measurements and controller updates is explored in controller analysis and design. This book offers the first systematic treatment of event-triggered sampled-data control system design using active disturbance rejection control (ADRC), an effective approach that is popular in both theoretic research and industrial applications. Extensive application examples with numerous illustrations are included to show how the event-triggered ADRC with theoretic performance guarantees can be implemented in engineering systems and how the performance can be actually achieved. For theoretic researchers and graduate students, the presented results provide new directions in theoretic research on event-triggered sampled-data systems; for control practitioners, the book offers an effective approach to achieving satisfactory performance with limited sampling rates.   From the Back Cover The past few years have seen the attention and rapid developments in event-triggered sampled-data systems, in which the effect of event-triggered sensor measurements and controller updates is explored in controller analysis and design. This book offers the first systematic treatment of event-triggered sampled-data control system design using active disturbance rejection control (ADRC), an effective approach that is popular in both theoretic research and industrial applications. Extensive application examples with numerous illustrations are included to show how the event-triggered ADRC with theoretic performance guarantees can be implemented in engineering systems and how the performance can be actually achieved. For theoretic researchers and graduate students, the presented results provide new directions in theoretic research on event-triggered sampled-data systems; for control practitioners, the book offers an effective approach to achieving satisfactory performance with limited sampling rates.   About the Author Dawei Shi received the B.Eng. degree in electrical engineering and its automation from the Beijing Institute of Technology, Beijing, China, in 2008, and the Ph.D. degree in control systems from the University of Alberta, Edmonton, AB, Canada, in 2014. In December 2014, he was appointed as Associate Professor at the School of Automation, Beijing Institute of Technology. From February 2017 to July 2018, he was with the Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, as Postdoctoral Fellow in bioengineering. Since July 2018, he has been with the School of Automation, Beijing Institute of Technology, as a Professor. His research focuses on analysis and synthesis of complex sampled-data control systems with applications to biomedical engineering, robotics, and motion systems. Dr. Shi serves as a Technical Editor/Associate Editor for IEEE/ASME Transactions on Mechatronics,  IET Control Theory & Applications, and IET Cyber-Systems & Robotics. He served as Associate Editor for IFAC World Congress and is a member of the IEEE Control Systems Society Conference Editorial Board. Yuan Huang was born in Heilongjiang, China, in 1992. He received the B.Eng. degree in process automation from the School of Chemical Engineering and Environment, Beijing Institute of Technology, Beijing, China, in 2014. He is currently working toward the Ph.D. degree in automation with the Beijing Institute of Technology. His research interests include event-triggered control, nonlinear control, and networked system control.  Junzheng Wang was born in Shaanxi, China, in 1964. He received the Ph.D. degree in control science and engineering from the Beijing Institute of Technology, Beijing, China, in 1994. He is Deputy Director with the Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology, w