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

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

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

Author(s) -

Huixin Liu,

Yonghua Lai,

Hongsong Lian,

Guobin Wang,

Dongsheng Zheng

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3589791

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

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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