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Designs 2018, 2(3), 31; https://doi.org/10.3390/designs2030031

A New Approach to Off-Line Robust Model Predictive Control for Polytopic Uncertain Models

School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai 201418, China
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Received: 9 July 2018 / Revised: 25 July 2018 / Accepted: 6 August 2018 / Published: 20 August 2018
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Abstract

Concerning the robust model predictive control (MPC) for constrained systems with polytopic model characterization, some approaches have already been given in the literature. One famous approach is an off-line MPC, which off-line finds a state-feedback law sequence with corresponding ellipsoidal domains of attraction. Originally, each law in the sequence was calculated by fixing the infinite horizon control moves as a single state feedback law. This paper optimizes the feedback law in the larger ellipsoid, foreseeing that, if it is applied at the current instant, then better feedback laws in the smaller ellipsoids will be applied at the following time. In this way, the new approach achieves a larger domain of attraction and better control performance. A simulation example shows the effectiveness of the new technique. View Full-Text
Keywords: polytopic model; model predictive control; off-line approach; domain of attraction polytopic model; model predictive control; off-line approach; domain of attraction
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Ma, X.; Bao, H.; Zhang, N. A New Approach to Off-Line Robust Model Predictive Control for Polytopic Uncertain Models. Designs 2018, 2, 31.

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