H∞ ILC Design for Discrete Linear Systems with Packet Dropouts and Iteration-Varying Disturbances

Abstract

An H∞ iterative learning controller is designed for networked systems with intermittent measurements and iteration-varying disturbances. By modeling the measurement dropout as a stochastic variable satisfying the Bernoulli random binary distribution, the design can be transformed into H∞ control of a 2D stochastic system described by Roesser model. A sufficient condition for mean-square asymptotic stability and H∞ disturbance attenuation performance for such 2D stochastic system is established by means of linear matrix inequality (LMI) technique, and formulas can be given for the control law design simultaneously. A numerical example is given to illustrate the effectiveness of the proposed results.