Iterative Learning Control Design of Switched Systems With Markovian Jump Parameters via Fuzzy Approach

In this paper, based on Takagi-Sugeno (T-S) approach the work is concerned with the iterative learning control (ILC) problem for a class of switched systems with data packet dropouts. The designed scheme is described by a class of Markovian switching systems with transition probabilities which are time-variant in a network environment. The links of network communications between controllerto-actuator (C/A) and sensor-to-controller (S/C) are unreliable. In terms of the construction of twodimensional (2D) T-S model, a novel composite strategy of 2D fuzzy iterative learning output feedback control is proposed. The sufficient conditions on stochastic stability are obtained by the 2D Lyapunov stability theory. Furthermore, the dynamics of the closed-loop are guaranteed to be stochastically stable and the desired H
_∞
performance is also provided. The solutions of the ILC controller are derived by the application of the cone complementarity linearisation (CCL) procedure. Finally, a numerical simulation is illustrated to show the validity of the design.