Input-to-state stabilizing nonlinear model-predictive-control based on affine control input
基于仿射控制输入的输入状态稳定非线性预测控制

The paper is concerned with a feedback model-predictive-control(MPC) scheme based on an affine control input for constrained nonlinear systems with disturbances. The control actions of MPC can be obtained by solving a min-max optimal problem of a finite horizon cost-function defined by an infinite norm. The robust stabilization of the closed-loop system is analyzed by the notion of input-to-state stability(ISS), and the determination of the upper bound of admissible disturbance is addressed. Finally, a numerical simulation shows the effectiveness of the MPC scheme.