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In this paper, a new on-line scheme is presented to design the optimalcoordination control for the consensus problem of multi-agent differentialgames by fuzzy adaptive dynamic programming (FADP), which brings together gametheory, generalized fuzzy hyperbolic model (GFHM) and adaptive dynamicprogramming. In general, the optimal coordination control for multi-agentdifferential games is the solution of the coupled Hamilton-Jacobi (HJ)equations. Here, for the first time, GFHMs are used to approximate the solution(value functions) of the coupled HJ equations, based on policy iteration (PI)algorithm. Namely, for each agent, GFHM is used to capture the mapping betweenthe local consensus error and local value function. Since our scheme uses thesingle-network rchitecture for each agent (which eliminates the action networkmodel compared with dual-network architecture), it is a more reasonablearchitecture for multi-agent systems. Furthermore, the approximation solutionis utilized to obtain the optimal coordination controls. Finally, we give thestability analysis for our scheme, and prove the weight estimation error andthe local consensus error are uniformly ultimately bounded. Further, thecontrol node trajectory is proven to be cooperative uniformly ultimatelybounded.

Leader-Based Optimal Coordination Control for the Consensus Problem of Multiagent Differential Games via Fuzzy Adaptive Dynamic Programming