Parallel Control for Continuous-Time Linear Systems: A Case Study

Qinglai Wei; Hongyang Li; Fei-Yue Wang

doi:10.1109/JAS.2020.1003216

Volume 7 Issue 4

Jun. 2020

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2020 > 7(4): 919-928

Qinglai Wei, Hongyang Li and Fei-Yue Wang, "Parallel Control for Continuous-Time Linear Systems: A Case Study," IEEE/CAA J. Autom. Sinica, vol. 7, no. 4, pp. 919-928, July 2020. doi: 10.1109/JAS.2020.1003216

Citation:

Qinglai Wei, Hongyang Li and Fei-Yue Wang, "Parallel Control for Continuous-Time Linear Systems: A Case Study," IEEE/CAA J. Autom. Sinica, vol. 7, no. 4, pp. 919-928, July 2020. doi: 10.1109/JAS.2020.1003216

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Parallel Control for Continuous-Time Linear Systems: A Case Study

doi: 10.1109/JAS.2020.1003216

Qinglai Wei^{1, 2, 3
,},
Hongyang Li^{1, 2, 3
,},
Fei-Yue Wang^4
,

1.
State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190
2.
University of Chinese Academy of Sciences, Beijing 100049
3.
Qingdao Academy of Intelligent Industries, Qingdao 266109, China
4.
Institute of Systems Engineering, Macau University of Science and Technology, Qingdao 266109, China

Funds:

the National Key Research and Development Program of China 2018AAA0101502

the National Key Research and Development Program of China 2018YFB1702300

the National Natural Science Foundation of China 61722312

the National Natural Science Foundation of China 61533019

the National Natural Science Foundation of China U1811463

the National Natural Science Foundation of China 61533017

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Author Bio:

Qinglai Wei(M'11) received the B.S. degree in automation, and the Ph.D. degree in control theory and control engineering, from Northeastern University, Shenyang, China, in 2002 and 2009, respectively. From 2009$-11, he was a Postdoctoral Fellow with the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China. He is currently a Professor of the institute and the Associate Director of the laboratory. He has authored four books, and published over 80 international journal papers. His research interests include adaptive dynamic programming, neural-networks-based control, optimal control, nonlinear systems and their industrial applications.
He is the Secretary of IEEE Computational Intelligence Society (CIS) Beijing Chapter since 2015. He was guest editors for several international journals. He was a recipient of IEEE/CAA Journal of Automatica Sinica Best Paper Award, IEEE System, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award, IEEE Transactions on Neural Networks and Learning Systems Outstanding Paper Award, the Outstanding Paper Award of Acta Automatica Sinica, IEEE 6th Data Driven Control and Learning Systems Conference (DDCLS2017) Best Paper Award, and Zhang Siying Outstanding Paper Award of Chinese Control and Decision Conference (CCDC). He was a recipient of Shuang-Chuang Talents in Jiangsu Province, China, Young Researcher Award of Asia Pacific Neural Network Society (APNNS), Young Scientist Award and Yang Jiachi Tech Award of Chinese Association of Automation (CAA). He is a Board of Governors (BOG) member of the International Neural Network Society (INNS) and a council member of CAA

Hongyang Li received the bachelor degree in automation from North China Electric Power University, Baoding, China, in 2016, and the master degree in control science and engineering from Tsinghua University, Beijing, China, in 2019. He is currently pursuing the Ph.D. degree in technology of computer applications with the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, and the University of Chinese Academy of Sciences, Beijing. His research interests include reinforcement learning, adaptive dynamic programming, optimal control, and neural networks. e-mail: lihongyang2019@ia.ac.cn

Fei-Yue Wang (S'87-M'89-SM'94-F'03) received the Ph.D. degree in computer and systems engineering from the Rensselaer Polytechnic Institute, Troy, NY, USA, in 1990. He joined the University of Arizona in 1990 and became a Professor and the Director of the Robotics and Automation Laboratory and the Program in Advanced Research for Complex Systems. In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China, and in 2002, was appointed as the Director of the Key Laboratory of Complex Systems and Intelligence Science, CAS. In 2011, he became the State Specially Appointed Expert and the Director of The State Key Laboratory for Management and Control of Complex Systems.
His current research focuses on methods and applications for parallel intelligence, social computing, and knowledge automation. He is a Fellow of INCOSE, IFAC, ASME, and AAAS. In 2007, he received the National Prize in Natural Sciences of China and became an Outstanding Scientist of ACM for his work in intelligent control and social computing. He received the IEEE ITS Outstanding Application and Research Awards in 2009 and 2011, respectively. In 2014, he received the IEEE SMC Society Norbert Wiener Award. Since 1997, he has been serving as the General or Program Chair of over 30 IEEE, INFORMS, IFAC, ACM, and ASME conferences. He was the President of the IEEE ITS Society from 2005 to 2007, the Chinese Association for Science and Technology, USA, in 2005, the American Zhu Kezhen Education Foundation from 2007 to 2008, the Vice President of the ACM China Council from 2010 to 2011, the Vice President and the Secretary General of the Chinese Association of Automation from 2008 to 2018. He was the Founding Editor-in-Chief (EiC) of the International Journal of Intelligent Control and Systems from 1995 to 2000, the IEEE ITS Magazine from 2006 to 2007, the IEEE/CAA Journal of Automatica Sinica from 2014 to 2017, and the China's Journal of Command and Control from 2015 to 2020. He was the EiC of the IEEE Intelligent Systems from 2009 to 2012, the IEEE Transactions on Intelligent Transportation Systems from 2009 to 2016, and is the EiC of the IEEE Transactions on Computational Social Systems since 2017, and the Founding EiC of China's Journal of Intelligent Science and Technology since 2019. Currently, he is the President of CAA's Supervision Council, IEEE Council on RFID, and Vice President of IEEE Systems, Man, and Cybernetics Society. e-mail: feiyue.wang@ia.ac.cn
Corresponding author:
Qinglai Wei, e-mail: qinglai.wei@ia.ac.cn
Recommended by Associate Editor Jun Zhang.
Received Date: 2020-05-08
Revised Date: 2020-06-09

Abstract

Abstract

In this paper, a new parallel controller is developed for continuous-time linear systems. The main contribution of the method is to establish a new parallel control law, where both state and control are considered as the input. The structure of the parallel control is provided, and the relationship between the parallel control and traditional feedback controls is presented. Considering the situations that the systems are controllable and incompletely controllable, the properties of the parallel control law are analyzed. The parallel controller design algorithms are given under the conditions that the systems are controllable and incompletely controllable. Finally, numerical simulations are carried out to demonstrate the effectiveness and applicability of the present method.
- Continuous-time linear systems,
- digital twin,
- parallel controller,
- parallel intelligence,
- parallel systems

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Recommended by Associate Editor Jun Zhang.

References(30)

References

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A new parallel control structure for continuous-time linear systems is proposed.
The parallel controller is proposed based on parallel control theory.
The parallel controller considers both system state and control as input.
The parallel controller can avoid the disadvantages of state feedback control.

Parallel Control for Continuous-Time Linear Systems: A Case Study

doi: 10.1109/JAS.2020.1003216

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通讯作者: 陈斌, bchen63@163.com

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