.png){kind=icon}
.png){kind=icon}
Return
Robust Model Predictive Control Using a Two-Step Triggering Scheme
.png){kind=icon}
PRE
AI
DOI：10.1109/TAC.2022.3170370.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
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.
Keywords:
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
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W