Iterative Learning-Based Formation Control for Multi-agent Systems with Locally Lipschitz Nonlinear Dynamics

Abstract

In this paper, the problem of formation control is considered for multi-agent systems subject to locally Lipschitz nonlinearities, for which a class of distributed iterative learning control (ILC) algorithms is proposed. By introducing a double-dynamics analysis (DDA) approach, the boundedness is ensured for the state and input of all agents such that a “quasi-globally” Lipschitz nonlinear condition can be established for the locally Lipschitz nonlinear multi-agent systems. This is further adopted to exploit the convergence of distributed ILC in order to achieve a perfect formation control of all agents. A simulation example is given to illustrate our ILC-based formation results and also the effectiveness of our DDA approach to convergence analysis of nonlinear ILC.