Title: Event-triggered robust model predictive control for trajectory tracking of omnidirectional mobile robot

Authors: Changrong Zhang; Juntong Yun; Du Jiang; Li Huang; Ying Liu; Bo Tao; Yuanmin Xie

Addresses: Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan, Hubei, China ' Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan, Hubei, China; Research Centre for Biomimetic Robot and Intelligent Measurement and Control, Wuhan University of science and Technology, Wuhan, Hubei, China ' Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of science and Technology, Wuhan, Hubei, China; College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China ' Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Wuhan, Hubei, China; College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei, China ' School of Mechanical Engineering, Hubei Engineering University, Xiaogan, Hubei, China ' Research Centre for Biomimetic Robot and Intelligent Measurement and Control, Wuhan University of science and Technology, Wuhan, Hubei, China; Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of science and Technology, Wuhan, Hubei, China ' Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan, Hubei, China; Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Wuhan, Hubei, China

Abstract: With the widespread application of Omnidirectional Mobile Robot (OMR) in fields such as industrial automation, logistics and services, the demand for trajectory tracking accuracy is increasingly stringent. This paper addresses the motion characteristics of OMR by proposing an event-triggered Model Predictive Control (MPC) approach, aiming to resolve the challenge of excessive computational resource requirements when solving the Optimal Control Problem (OCP) online for omnidirectional mobile robots. The proposed method comprises two core components: a Robust Model Predictive Control (RMPC) controller and a variable time-domain event-triggering mechanism. The robust MPC controller ensures strong disturbance rejection capabilities for OMR under external disturbances by employing a tightened constraint strategy. Simultaneously, the introduction of a prediction horizon update strategy and an event-triggering mechanism effectively alleviates the computational burden of solving the OCP online. This method significantly reduces computational resource consumption while maintaining control performance, thereby enhancing the real-time trajectory tracking of OMR. Simulation experiments demonstrate that, compared to traditional event-triggered MPC (EMPC) methods, the computational load is reduced by up to 76.53%, validating the efficiency and feasibility of the proposed method in practical applications.

Keywords: model predictive control; event-triggered mechanism; omnidirectional mobile robot; trajectory tracking.

DOI: 10.1504/IJWMC.2025.149193

International Journal of Wireless and Mobile Computing, 2025 Vol.29 No.4, pp.385 - 394

Received: 02 Jan 2025
Accepted: 24 Feb 2025
Published online: 17 Oct 2025 *

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