Consensus tracking via quantized iterative learning control for singular nonlinear multi-agent systems with state time-delay and initial state error

Abstract

This paper investigates the quantized iterative learning consensus tracking problem for singular nonlinear multi-agent systems (MASs) in the presence of state time-delay and initial state error. The unified D-type quantized learning control protocols based on the initial state learning with index gain is proposed and employed for singular nonlinear MASs with state time-delay in both continuous-time domain and discrete-time domain. Based on the operator theory, the convergence condition of the consensus tracking errors between each follower agent and the leader is manifested and analyzed over a fixed time interval. Furthermore, the closed-loop D-type learning protocols are introduced to track the leader’s trajectory in order to compare the convergent rate with the variable index gain learning protocols. Finally, simulation results are applied to confirm the validity of the proposed protocols.