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This work addresses the multi-agent consensus tracking problem by iterative learning control (ILC) with input sharing. In many ILC works for multi-agent coordination problem, each agent maintains its own input learning, and the input signal is corrected by local measurements over iteration domain. If the agents are allowed to share their learned inputs among them, the strategy can improve the learning...
This work addresses a leader-follower tracking problem by an iterative learning control approach. In the multi-agent setup, a dynamic leader is connected to a few of followers, and the communication among agents is described by a directed graph. In contrast to many existing literature in which the perfect initial condition is imposed, we assume that the initial state is reset to a fixed position that...
In this paper, under repeatable operation environment, an iterative learning control (ILC) scheme is applied for multi-agent systems (MAS) to perform consensus tracking, where the underline communication graph is assumed to be fixed and directed. Different from many existing consensus schemes for linear agent dynamics, we consider time-varying nonlinear agent models with non-parametric uncertainties...
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