Robust Model Predictive Control Using a Two-Step Triggering Scheme

• 成果类型: Article
• 署名作者: Deng, Li; Shu, Zhan; Chen, Tongwen
• 署名单位: University of Alberta
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3170370
• 发表日期: 2023
• 页码: 1934-1940
• 关键词: Robust stability; predictive models; mathematical models; Predictive control; optimal control; discrete-time systems; cost function; robust model predictive control (MPC); robust positively invariant sets; two-step triggering

摘要

This article is concerned with event-triggered robust model predictive control for linear discrete-time systems with bounded disturbances. A two-step scheme involving a tentative verification of a triggering condition and a delayed triggering with a waiting horizon is proposed to reduce the average triggering rate and fully utilize the nominal optimal control sequence minimizing a quadratic cost function. The triggering condition and the waiting horizon are synthesized based on a prediction model of the plant and a robust positively invariant set associated with it. Under mild conditions, recursive feasibility and closed-loop robust stability are guaranteed. Two examples are used to show the effectiveness and merits of the proposed approach.