Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
696106 | Automatica | 2014 | 12 Pages |
Abstract
We consider inherent robustness properties of model predictive control (MPC) for continuous-time nonlinear systems with input constraints and terminal constraints. We show that MPC with a nominal prediction model and persistent but bounded disturbances has some degree of inherent robustness when the terminal control law and the terminal penalty matrix are chosen as the linear quadratic control law and the related Lyapunov matrix, respectively. We emphasize that the input constraint sets can be any compact set rather than convex sets, and our results do not depend on the continuity of the optimal cost function or of the control law in the interior of the feasible region.
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Authors
Shuyou Yu, Marcus Reble, Hong Chen, Frank Allgöwer,