Work

Mixed Time/Event-Triggered Model Predictive Tracking Control for Networked Mobile Robots

Year: 2025

Type: article

Abstract: Focusing on the tracking control challenges in networked mobile robot systems, this research formulates a mixed time/event-triggered model predictive control (MPC) method. The method integrates time-triggered and event-triggered mechanisms, where the time-triggered module improves the performance of the MPC, and the event-triggered module reduces the resource consumption without sacrificing the control performance. The MPC algorithm is developed based on the auxiliary optimization problem (OP), which is constrained by linear matrix inequalities. The feasibility of the auxiliary OP is evaluated, and the mean square stability of the closed-loop system is investigated. The research results are expected to save network resources while ensuring the performance of networked mobile robots and provide strong support for practical applications of networked mobile robots.

Source: IEEE Access

DOI: 10.1109/access.2025.3589791

Authors: Huixin Liu, Yonghua Lai, Hongsong Lian, Guobin Wang, Dongsheng Zheng

Institution: State Grid Corporation of China (China)

Language: English

Topic: Stability and Control of Uncertain Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,075

Funder: State Grid Fujian Electric Power Company