Event-triggered iterative learning containment control for one-sided Lipschitz nonlinear singular switched multi-agent systems with multiple leaders and error quantization

In this work, under a repeatable control environment, the iterative learning containment control issue for multi-agent systems with one-sided Lipschitz nonlinear singular switched dynamics is addressed. It focuses on the output containment for one-sided Lipschitz nonlinear singular switched multi-agent systems (SWMASs) with multiple leaders, for which an event-triggered containment quantized iterative learning control (QILC) scheme is designed. Due to the limited system resources, SWMASs are often restricted in their communication capabilities and the frequency of controller updates in many applications, the proposed event-triggering mechanism can greatly restrict the use of communication and computation resources throughout the iterative learning process. When the triggering requirement is met, the event-triggered QILC input is repeatedly updated; alternatively, the control input stays unchanged. To conquer the nonidentical initial states of followers, an initial state learning with error quantization and event-triggering is also utilized. By virtue of some appropriate learning gains and sufficient convergent conditions, the containment error convergence can be accomplished for one-sided Lipschitz SWMASs. Finally, some numerical examples via Matlab are provided to demonstrate the efficacy of the event-triggered QILC scheme, it indicates that followers’ outputs can converge to the convex hull formed by leaders and the containment errors gradually converge to the 10−3 - vicinity of the origin along the iteration axis, where the communication resources can save more than 50% in the transmission channel.