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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Vydáno v:IET control theory & applications Ročník 13; číslo 9; s. 1336 - 1343
Hlavní autoři: Su, Yanxu, Wang, Qingling, Sun, Changyin
Médium: Journal Article
Jazyk:angličtina
Vydáno: The Institution of Engineering and Technology 11.06.2019
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ISSN:1751-8644, 1751-8652
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Abstract 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.
AbstractList 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.
Author Sun, Changyin
Wang, Qingling
Su, Yanxu
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  email: cysun@seu.edu.cn
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Issue 9
Keywords 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
Language English
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Snippet A self-triggered model predictive control (MPC) scheme for continuous-time perturbed nonlinear systems subject to bounded disturbances is investigated in this...
A self‐triggered model predictive control (MPC) scheme for continuous‐time perturbed nonlinear systems subject to bounded disturbances is investigated in this...
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wiley
iet
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StartPage 1336
SubjectTerms 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
Title Self-triggered robust model predictive control for nonlinear systems with bounded disturbances
URI http://digital-library.theiet.org/content/journals/10.1049/iet-cta.2018.5459
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Volume 13
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