Optimal Distributed Synchronization Control for Heterogeneous Multi-agent Graphical Games
In this chapter, a new optimal coordination control for the consensus problem of heterogeneous multi-agent differential graphical games by iterative ADP is developed. The main idea is to use iterative ADP technique to obtain the iterative control law which makes all the agents track a given dynamics and simultaneously makes the iterative performance index function reach the Nash equilibrium. In the developed heterogeneous multi-agent differential graphical games, the agent of each node is different from the one of other nodes. The dynamics and performance index function for each node depend only on local neighbor information. A cooperative policy iteration algorithm for graphical differential games is developed to achieve the optimal control law for the agent of each node, where the coupled Hamilton–Jacobi (HJ) equations for optimal coordination control of heterogeneous multi-agent differential games can be avoided. Convergence analysis is developed to show that the performance index functions of heterogeneous multi-agent differential graphical games can converge to the Nash equilibrium. Simulation results will show the effectiveness of the developed optimal control scheme.