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Robust Model Predictive Control Using a Two-Step Triggering Scheme
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DOI：10.1109/TAC.2022.3170370.png)
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摘要
En 中文
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.
Keyword:
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