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

IF 3.4 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Access Pub Date : 2025-07-16 DOI:10.1109/ACCESS.2025.3589791

Huixin Liu;Yonghua Lai;Hongsong Lian;Guobin Wang;Dongsheng Zheng

引用次数: 0

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.

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网络移动机器人的混合时间/事件触发模型预测跟踪控制

针对网络化移动机器人系统的跟踪控制问题，提出了一种时间/事件触发混合模型预测控制方法。该方法集成了时间触发和事件触发机制，其中时间触发模块提高了MPC的性能，事件触发模块在不牺牲控制性能的情况下减少了资源消耗。MPC算法是在线性矩阵不等式约束下的辅助优化问题（OP）的基础上开发的。评估了辅助OP的可行性，并研究了闭环系统的均方稳定性。研究成果有望在保证网络化移动机器人性能的同时节省网络资源，为网络化移动机器人的实际应用提供有力支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Access COMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC

CiteScore

9.80

自引率

7.70%

发文量

6673

审稿时长

6 weeks

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