Two‐step MPC for systems with input non‐linearity and norm‐bounded disturbance. Issue 2 (1st January 2019)

• Record Type: Journal Article
• Authors: Wang, Jun; Ding, Baocang; Wang, Yong
• Is Part Of: IET control theory & applications. Volume 13:Issue 2(2019)
• Page Start: 183
• Page End: 190
• Publication Date: 2019-01-01
• Subjects: predictive control -- linear algebra -- stability -- nonlinear control systems -- iterative methods -- closed loop systems -- Riccati equations -- control nonlinearities -- linear systems; input nonlinearity -- norm‐bounded disturbance -- two‐step model predictive control -- linear part -- unconstrained MPC problem -- desaturation -- Hammerstein systems -- two‐step MPC -- Riccati iterative equation -- nonlinear algebraic equation -- quadratic boundedness technique -- stability -- intermediate control law -- closed‐loop system stability -- quadratic convergence -- quadratic cost function minimisation -- sufficient conditions; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2018.5091
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : 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.