Robust ℋ∞ horizon optimization control for sampled-data systems with constraints

In this paper, the problem of designing of robust state-feedback H_∞ controller for uncertain sampled-data control systems with output constraints have been investigated base on jump system model of sampled-data system using constant Lyapunov function (CLF) approach. The online algorithm of the H_∞ receding horizon optimization design for the norm-bounded parametric uncertain system is proposed. The optimal state-feedback H_∞ controllers are obtained and these controller can provide a performance tradeoff with respect to output constraints, i.e., the control strategy offers the capability of relaxing the performance level automatically in order to obey output constraints in the case of a larger disturbance. When the disturbance is restored to a usual situation, this control strategy can also improve the performance of system automatically.