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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Veröffentlicht in:	IET control theory & applications Jg. 13; H. 9; S. 1336 - 1343
Hauptverfasser:	Su, Yanxu, Wang, Qingling, Sun, Changyin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 11.06.2019
Schlagworte:	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
Online-Zugang:	Volltext
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