Decentralized adaptive iterative learning control for uncertain interconnected systems with state delay

Base on the uncertain interconnected systems with state delay, a decentralized model reference adaptive iterative learning control is proposed in this paper. The proposed controller of each subsystem only relies on local state variables with no any information exchanges with other subsystems. In order to eliminate the effects of interconnections, state delays and uncertainties, the adaptive parameters are updated along iteration axis. Simulation results demonstrate, utilizing the proposed adaptive controller, the tracking error for each subsystem converges along the iteration axis.