Adaptive Control of Complex Electromechanical Systems and Its Applications

Erscheinungsjahr 2027
ISBN: 978-0-443-49195-5
Verlag: Elsevier Science

Buch, Englisch, 300 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 449 g

Adaptive Control of Complex Electromechanical Systems and Its Applications addresses the critical challenges of controlling nonlinear electromechanical systems that exhibit nonlinearities, parameter uncertainties, and external disturbances. This reference provides a thorough tutorial on adaptive parameter estimation, disturbance rejection, and transient performance enhancement, effectively bridging the gap between advanced theory and practical engineering applications. It offers detailed guidance on modeling non-smooth dynamics and designing robust adaptive controllers. The book benefits graduate students, researchers, and practicing engineers by presenting state-of-the-art algorithms and control strategies such as adaptive backstepping, disturbance observers, sliding mode control, and multi-motor driving systems. Supported by practical examples and experimental validation, it equips readers with the tools needed to improve control accuracy, robustness, and dynamic response in complex electromechanical systems. This resource facilitates rapid mastery of adaptive control techniques and supports innovation in research and industrial applications.

Autoren/Hrsg.

Wang, Shubo

Na, Jing

Ren, Xuemei

Chen, Qiang

Hu, Shuangyi

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau

Inhaltsverzeichnis

1. Introduction
2. Adaptive Control for Servo System with Unknown Dynamics
3. Adaptive Parameter Estimation and Control for Complex Electromechanical Systems
4. Disturbance Rejection and Control for Servo Mechanisms Systems
5. Prescribed Performance Control for Complex Electromechanical Systems
6. Multi-Motor Driving Control
7. Conclusion

Über Autor(innen)

Hu, Shuangyi
Dr. Shuangyi Hu earned his B.S. in Automation and Ph.D. in Control Science and Engineering from Beijing Institute of Technology in 2017 and 2023, respectively. He is currently a Research Fellow at Zhejiang University of Technology. His research interests include adaptive control, repetitive learning control, and motor-drive servo systems.

Wang, Shubo
Shubo Wang received the Ph.D. degree in control science and engineering from the Beijing Institute of Technology, Beijing, China, in 2017. From 2017 to 2024, he was with the School of Automation, Qingdao University, Qingdao, China, where he became a Full Professor in 2023. He has been with the Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, China, since 2024. He has coauthored one monograph and more than 70 international journal and conference papers. His current research interests include adaptive control, parameter estimation, neural network, servo system, robotic, nonlinear control, and applications for robotics and motor driving systems.

Ren, Xuemei
Xuemei Ren received her B.S. degree from Shandong University, Shandong, China, in 1989, and M.S. and Ph.D. degrees in control engineering from the Beijing University of Aeronautics and Astronautics, Beijing, China, in 1992 and 1995, respectively. She worked at the School of Automation, Beijing Institute of Technology as a professor from 2002. She has published more than 100 academic papers. Her research interests include nonlinear systems, intelligent control, neural network control, adaptive control, multi- drive servo systems and time delay systems.

Na, Jing
Jing Na received his B.Eng. and Ph.D. degrees from the School of Automation, Beijing Institute of Technology, Beijing, China, in 2004 and 2010, respectively. He was a Monaco/ITER Postdoctoral Fellow at the ITER Organization, Saint-Paul-lès-Durance, France, and also a Marie Curie Intra-European Fellow with the Department of Mechanical Engineering, University of Bristol, U.K. Since 2010, he has been with the Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, China, where he became a professor in 2013. He has co-authored one monograph and more than 100 international journal and conference papers. His current research interests include intelligent control, adaptive parameter estimation, nonlinear control.

Chen, Qiang
Qiang Chen received the B.S. degree in measure and control technology and instrumentation from Hebei Agricultural University, Baoding, China, in 2006, and the Ph.D. degree in control science and engineering from Beijing Institute of Technology, Beijing, China, in 2012. Since 2012, he has been with the College of Information Engineering, Zhejiang University of Technology, Hangzhou, China, where he was a Professor in 2022. He has published over 100 peer-reviewed papers in journals and conference proceedings. He has been authorized more than 60 invention patents, 13 of which were transferred. His research interests include adaptive control and iterative learning control with application to motion control systems.