Regular Papers

International Journal of Control, Automation and Systems 2022; 20(10): 3433-3444

Published online September 30, 2022

https://doi.org/10.1007/s12555-021-0726-4

© The International Journal of Control, Automation, and Systems

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

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

University of Electronic Science and Technology of China

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. "

Keywords Model predictive control, optimal control, swarm intelligence, time-varying linear systems.

Article

Regular Papers

International Journal of Control, Automation and Systems 2022; 20(10): 3433-3444

Published online October 1, 2022 https://doi.org/10.1007/s12555-021-0726-4

Copyright © The International Journal of Control, Automation, and Systems.

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

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

University of Electronic Science and Technology of China

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. "

Keywords: Model predictive control, optimal control, swarm intelligence, time-varying linear systems.

IJCAS
May 2024

Vol. 22, No. 5, pp. 1461~1759

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