Optimal formation control for second-order nonlinear MASs with collision avoidance and connectivity assurance

In this paper, the optimal formation control issue with collision avoidance and connectivity assurance is investigated for a class of second-order uncertain nonlinear multi-agent systems. First, the neural networks are employed in order to deal with the unknown nonlinear dynamics of the system. Then, an optimal formation control scheme is developed in the framework of the identifier–actor–critic. By constructing a new performance metric function containing collision avoidance and connectivity constraints, it is demonstrated that asymptotic convergence of the tracking error can be achieved under the proposed control scheme. Finally, the effectiveness of the proposed control method is validated by the numerical simulation example.