Interpolation Model Predictive Control of Nonlinear Systems Described by Quasi-LPV Model
- Autores: Meng Zhao 1, Jiang C.1, Tang X.2, She M.3
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Afiliações:
- College of Mechanical and Electrical Engineering, Hainan University
- College of Automation, Chongqing University of Posts and Telecommunications
- College of Automation, Chongqing University
- Edição: Volume 52, Nº 5 (2018)
- Páginas: 354-364
- Seção: Article
- URL: https://journal-vniispk.ru/0146-4116/article/view/175533
- DOI: https://doi.org/10.3103/S0146411618050085
- ID: 175533
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Resumo
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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Sobre autores
Meng Zhao
College of Mechanical and Electrical Engineering, Hainan University
Autor responsável pela correspondência
Email: meng.zh@outlook.com
República Popular da China, Haikou, 570228
Canchen Jiang
College of Mechanical and Electrical Engineering, Hainan University
Email: meng.zh@outlook.com
República Popular da China, Haikou, 570228
Xiaoming Tang
College of Automation, Chongqing University of Posts and Telecommunications
Email: meng.zh@outlook.com
República Popular da China, Chongqing, 40031
Minghong She
College of Automation, Chongqing University
Email: meng.zh@outlook.com
República Popular da China, Chongqing, 40044
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