Abstract
This paper considers the problem of event-driven robust output feedback model predictive control for constrained linear systems subject to bounded disturbances. The proposed output feedback controller involves designing a Luenberger state estimator and an event-driven robust model predictive controller. The state estimation error is bounded by a robust positively invariant set, and a constraint tightening method is utilized to formulate the robust output feedback MPC optimization problem. Based on input-to-state stability theory, the event-triggering condition with respect to the error between the system output and the observer output is derived. At each sampling instant, the optimization problem is required to be solved only when the triggering condition is violated. Otherwise, a candidate control law is constructed and applied to system. Moreover, both the feasibility of the optimization problem and the convergence of closed-loop system are proved. Finally, a simulation example is given to show that the proposed approach can reduce the solving frequency of optimization problems while guaranteeing that the system state converges to a neighborhood of the equilibrium.
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Acknowledgments
This work is partly supported by National Natural Science Foundation (NNSF) from China (61374107, 61273073), the Fundamental Research Funds for the Central Universities and the Program of Shanghai Subject Chief Scientist (14XD1420900).
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Lu, L., Zou, Y. & Niu, Y. Event-Driven Robust Output Feedback Control for Constrained Linear Systems via Model Predictive Control Method. Circuits Syst Signal Process 36, 543–558 (2017). https://doi.org/10.1007/s00034-016-0316-5
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DOI: https://doi.org/10.1007/s00034-016-0316-5