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

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 o...

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Vydané v:	IET control theory & applications Ročník 13; číslo 9; s. 1336 - 1343
Hlavní autori:	Su, Yanxu, Wang, Qingling, Sun, Changyin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	The Institution of Engineering and Technology 11.06.2019
Predmet:	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
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