Two-step MPC for systems with input non-linearity and norm-bounded disturbance

In this study, a novel two-step model predictive control (MPC) for Hammerstein systems subject to norm-bounded disturbance is addressed. In the first step, the intermediate control law for the linear part of the system is posed as the solution to the unconstrained MPC problem that minimises a quadra...

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Bibliographic Details
Published inIET control theory & applications Vol. 13; no. 2; pp. 183 - 190
Main Authors Wang, Jun, Ding, Baocang, Wang, Yong
Format Journal Article
LanguageEnglish
Published The Institution of Engineering and Technology 29.01.2019
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ISSN1751-8644
1751-8652
1751-8652
DOI10.1049/iet-cta.2018.5091

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Summary:In this study, a novel two-step model predictive control (MPC) for Hammerstein systems subject to norm-bounded disturbance is addressed. In the first step, the intermediate control law for the linear part of the system is posed as the solution to the unconstrained MPC problem that minimises a quadratic cost function over a given finite time, for which the solution is determined by a novel Riccati iterative equation. In the second step, the actual control move is obtained by solving non-linear algebraic equation group and desaturation. The quadratic boundedness technique is used to specify the stability for closed-loop system with norm-bounded disturbance, and the sufficient conditions for quadratic convergent of the system state are presented. Simulation results demonstrate the effectiveness of the proposed approach to this class of systems.
ISSN:1751-8644
1751-8652
1751-8652
DOI:10.1049/iet-cta.2018.5091