Iterative Learning Control for Locally Lipschitz Nonlinear Fractional-order Multi-agent Systems

Abstract In this paper, we design P-type and PIβ-type iterative learning control update laws to deal with the consensus tacking problem for nonlinear fractional-order multi-agent systems with both fixed and iteration-varying communicating graphs. The leader-follower model is used in the communication graph of the multi-agent system. The nonlinear function in each agent is required to be locally Lipschitz condition only. Sufficient conditions are proposed to guarantee the asymptotical output consensus. Numerical simulations are conducted to verify the theoretical analysis.