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Interpolation Model Predictive Control of Nonlinear Systems Described by Quasi-LPV Model

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Abstract

This paper investigates the interpolation model predictive control (MPC) algorithm for nonlinear discrete-time systems, which can be represented by affine linear parameter varying (LPV) model. The general nonlinear model is transformed into the quasi-LPV model, then the equivalent polytopic LPV model and disturbed Linear time-invariant (LTI) model are obtained. Therefore, a finite-horizon interpolation MPC algorithm based ellipsoidal invariant set (EIS) is proposed. For comparison, the existing zero-horizon interpolation MPC algorithm, based on EIS, is also described to display the advantages of proposed algorithm. By virtue of the finite-horizon technique, the feasible region of proposed algorithm is much larger than zero-horizon interpolation MPC algorithm. An illustrative example is given to verify the effectiveness of proposed algorithms.

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ACKNOWLEDGMENTS

This work was supported by the Natural Science Foundation of Hainan Province of China (grant no. 20166213), National Natural Science Foundation of China (grant no. 61403055), Research Project of Chongqing Science and Technology Commission (grant no. cstc2014jcyjA40005), and the Scientific Research Foundation of Hainan University (grant no. kyqd1575).

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Authors and Affiliations

  1. College of Mechanical and Electrical Engineering, Hainan University, 570228, Haikou, China

    Meng Zhao & Canchen Jiang

  2. College of Automation, Chongqing University of Posts and Telecommunications, 40031, Chongqing, China

    Xiaoming Tang

  3. College of Automation, Chongqing University, 40044, Chongqing, China

    Minghong She

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  1. Meng Zhao
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  2. Canchen Jiang
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  3. Xiaoming Tang
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  4. Minghong She
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Correspondence to Meng Zhao.

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Meng Zhao, Jiang, C., Tang, X. et al. Interpolation Model Predictive Control of Nonlinear Systems Described by Quasi-LPV Model. Aut. Control Comp. Sci. 52, 354–364 (2018). https://doi.org/10.3103/S0146411618050085

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