Consensus Control of Multi-Agent Systems with Nonlinear Dynamics and Input Constraints

In this paper, the consensus problem of multi-agent systems with nonlinear dynamics and input constraints is addressed. First, a general control protocol for the consensus achieving of the multi-agent systems without input constraints is proposed. And then, we consider the case that the input of the multi-agent systems is constrained. Two compensators who are fuzzy compensator and Radial Basis Function (RBF) network compensator are applied to compensate the control input errors. The new control protocols are designed via introducing the estimation of errors; and the convergence of the proposed control protocols is analyzed by sliding mode control approach and Lyapunov stability theory. Finally, three cases are provided to illustrate the effectiveness of the theoretical analysis.