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Model Predictive Control for Tracking Bounded References With Arbitrary Dynamics
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DOI：10.1109/tac.2026.3662309.png)
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Abstract
En 中文
In this article, a model predictive control (MPC) method is proposed for constrained linear systems to track bounded references generated by linear exosystems with arbitrary Lyapunov stable dynamics. In the proposed method, sudden changes in reference are taken into account and are addressed by introducing an artificial reference as an additional decision variable. The cost function penalizes both the artificial state error and the reference error, while the terminal constraint is imposed on the artificial state error and the artificial reference. We specify the requirements for the terminal constraint and the cost function to guarantee recursive feasibility of the proposed method and asymptotic stability of the tracking error. Then, periodic and nonperiodic references are analyzed, and methods are developed to determine the required cost function and terminal constraint. Finally, the efficiency of the proposed MPC controller is demonstrated with simulation examples.
Keywords:
Constrained control
linear systems
predictive control for linear systems
reference tracking
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W
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