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Swarm Intelligence Based Model Predictive Control Strategy for Optimal State Control of Discrete Time-varying MIMO Linear Systems

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Abstract

It is a challenging task to effectively control multi-input and multi-output (MIMO) discrete time-varying linear systems. This paper proposes a swarm intelligence based model predictive control (MPC) strategy for addressing the challenge. First, a swarm intelligence based iterative dynamic optimal control solver is proposed to avoid the difficulty in solving the algebraic Riccati equation of finite-horizon optimal state control problem. Then, a swarm intelligence based online optimal controller is designed based on the MPC strategy, which can extend the optimal control problem from the finite-horizon to the infinite-horizon. Finally, the feedback structure of the online optimal state control system for MIMO discrete time-varying linear systems is constructed. A real-time simulation and a practical control experiment of a first order inverted pendulum system are employed to elborate the proposed method. The results show that the proposed method has the high efficiency, high accuracy, and anti-interference capability.

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Authors and Affiliations

  1. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Hao Zheng, Yanwei Zhang, Haider Muhammad Husnain, Pengpeng Zhi & Zhonglai Wang

  2. Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou, 313001, China

    Hao Zheng & Zhonglai Wang

Authors
  1. Hao Zheng
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  2. Yanwei Zhang
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  3. Haider Muhammad Husnain
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  4. Pengpeng Zhi
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  5. Zhonglai Wang
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Correspondence to Zhonglai Wang.

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This work was supported by Sichuan Science and Technology Program under the Contract No. 2020JDJQ0036 and Natural Science Foundation of Sichuan Province under the Contract No. 2022NSFSC1941.

Hao Zheng was born in Chengdu, China. He received his B.Eng. degree in mechanical engineering from University of Electronic Science and Technology of China, Chengdu, China, in 2018. He is currently pursuing a Ph.D. degree with the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu. He has worked on the attitude and position control, and the energy systems control strategy on flapping-wing micro air vehicles. His current research interests include model predictive control, nonlinear system optimal control, and heuristic optimization algorithm.

Yanwei Zhang was born in Shandong, China, in 1993. He received his B.S. degree in mechanical engineering from University of Electronic Science and Technology of China in 2016. And he started a successive master’s and doctoral programs in 2016. He is currently pursuing a Ph.D. degree in University of Electronic Science and Technology of China. He has been a joint Ph.D. student with the Department of Mechanical Engineering, Delft University of Technology, Netherlands. He also works as a Research Assistant with the Laboratory of Advanced Design Group, University of Electronic Science and Technology of China. His research is focused on fluid dynamics, optimization design, and reliability control of flapping-wing micro air vehicle.

Haider Muhammad Husnain is currently a postgraduate research fellow at the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China. He received his B.Eng. degree in mechatronics from Air University, Islamabad, Pakistan, and Master’s degree in Control Science and Engineering from UESTC, in 2015 and 2019, respectively. He earned first prizes in the ‘Academic Excellence Award 2018’ and ‘Excellent Performance Award 2018’ from the UESTC on his outstanding performance in studies as well in social and volunteer services severally. He was a recipient of the Higher Education Commission, Pakistan, Scholarship and Chinese Government Scholarship, in 2012 and 2017. His research areas include robotics, navigation, and autonomous systems.

Pengpeng Zhi is currently a postdoc at the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China. He received his B.S. degree in automobile service engineering from Anyang Institute of Technology in 2014, and a Ph.D. degree from Dalian Jiaotong University in 2021. He has published more than 20 journal papers. His main research interests include CAE key technologies and rail transit safety control.

Zhonglai Wang was born in Shandong, China. He received his Ph.D. degree from University of Electronic Science and Technology of China in 2009. Currently, he is a full professor at School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China. He has published over 50 peer-reviewed journal papers and in charge of over 20 projects as PI. His research interests include reliability-based design, robust control of flapping-wing micro air vehicle, design optimization under uncertainty, and model validation.

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Zheng, H., Zhang, Y., Husnain, H.M. et al. Swarm Intelligence Based Model Predictive Control Strategy for Optimal State Control of Discrete Time-varying MIMO Linear Systems. Int. J. Control Autom. Syst. 20, 3433–3444 (2022). https://doi.org/10.1007/s12555-021-0726-4

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