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Electrical Engineering and Systems Science > Systems and Control
Title: A Semi-Definite Programming Approach to Robust Adaptive MPC under State Dependent Uncertainty
(Submitted on 10 Oct 2019 (v1), last revised 15 Feb 2020 (this version, v2))
Abstract: We propose an Adaptive MPC framework for uncertain linear systems to achieve robust satisfaction of state and input constraints. The uncertainty in the system is assumed additive, state dependent, and globally Lipschitz with a known Lipschitz constant. We use a non-parametric technique for online identification of the system uncertainty by approximating its graph via envelopes defined by quadratic constraints. At any given time, by solving a set of convex optimization problems, the MPC controller guarantees robust constraint satisfaction for the closed loop system for all possible values of system uncertainty modeled by the envelope. The uncertainty envelope is refined with data using Set Membership Methods. We highlight the efficacy of the proposed framework via a detailed numerical example.
Submission history
From: Monimoy Bujarbaruah [view email][v1] Thu, 10 Oct 2019 06:07:06 GMT (269kb,D)
[v2] Sat, 15 Feb 2020 23:36:23 GMT (286kb,D)
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