Quantized Consensus Control for Second-Order Nonlinear Multi-agent Systems with Sliding Mode Iterative Learning Approach

In this paper, the consensus problem of second-order nonlinear multi-agent systems with directed communication topology is discussed. Information for the states of neighbour agents is quantized using a uniform quantizer. The sliding mode control law is designed based on quantized state information and the stability analyzed by using Lyapunov theory. Additionally, an iterative learning control law based on sliding mode errors is developed. Thereby, a novel consensus control protocol consisting of a sliding mode control law and an iterative learning approach is achieved, where the purpose of applying the sliding mode control law is to eliminate non-repeatable uncertainties and the iterative learning control law is to remove repeatable disturbances. Also, the convergence of the proposed control protocol is analyzed in the frequency domain. Finally, two cases are provided to illustrate the effectiveness of theoretical analysis.