Two-step MPC for systems with input nonlinearity 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 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. [ABSTRACT FROM AUTHOR]