Self-triggered robust model predictive control for nonlinear systems with bounded disturbances

• Published in: IET control theory & applications Vol. 13; no. 9; pp. 1336 - 1343
• Main Authors: Su, Yanxu, Wang, Qingling, Sun, Changyin
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 11.06.2019
• Subjects: bounded disturbances; closed loop systems; continuous time systems; continuous‐time perturbed nonlinear systems; control system synthesis; current sampled state; disturbance; dual‐mode approach; inter‐execution time; model predictive control scheme; MPC algorithm; nonlinear control systems; nonlinear systems; optimal control; optimal control trajectory; optimisation; optimisation problem; perturbed closed‐loop system; prediction horizon; predictive control; robust control; robust model predictive control; self‐triggered robust model predictive control; self‐triggered strategy; Special Issue: Recent Advances in Control and Verification for Hybrid Systems; stability; disturbance; robust model predictive control; current sampled state; optimisation problem; self-triggered strategy; optimisation; robust control; optimal control trajectory; continuous-time perturbed nonlinear systems; continuous time systems; stability; self-triggered robust model predictive control; optimal control; control system synthesis; MPC algorithm; model predictive control scheme; closed loop systems; dual-mode approach; nonlinear systems; prediction horizon; nonlinear control systems; inter-execution time; perturbed closed-loop system; predictive control; bounded disturbances
• ISSN: 1751-8644; 1751-8652
• DOI: 10.1049/iet-cta.2018.5459

A self-triggered model predictive control (MPC) scheme for continuous-time perturbed nonlinear systems subject to bounded disturbances is investigated in this study. A self-triggered strategy is designed to obtain the inter-execution time before the next trigger using the current sampled state. An optimisation problem is addressed to obtain the optimal control trajectory at each triggered instant. The so-called dual-mode approach is used to stabilise the perturbed closed-loop system. Furthermore, sufficient conditions are derived to ensure the feasibility and stability, respectively. It is shown that with a properly designed prediction horizon, the feasibility of the proposed self-triggered MPC algorithm can be guaranteed if the disturbance is bounded in a small enough area. Meanwhile, the stability is proved under the self-triggered condition. Finally, a numerical example is given to illustrate the efficacy of the authors proposed scheme.