Sampled-data State-feedback Control under Disturbances and Measurement Noises^⋆

A novel sampled-data state-feedback control law for linear systems under disturbances and measurement noises is proposed. The control law is based on a new state estimator that rejects the influence of disturbances and noises. Differently from existing results, the ultimate bound depends only on a magnitude of a single component of a noise vector. The conditions for the input-to-state stability are presented in terms of LMIs. Additionally, we propose the algorithm for calculation of the optimal controller parameters for minimization of the ultimate bound and the calculation criteria for the admissible sampling time. Efficiency of the proposed method is illustrated by the numerical example and compared with an existing one.