Adaptive Fixed‐Time Bipartite Containment Control for Saturated Nonlinear Multi‐Agent Systems Based on Optimized Backstepping Technique

ABSTRACT This paper studies the fixed‐time optimal bipartite containment control problem for nonlinear multi‐agent systems (MASs) with input saturation. First, the conventional bipartite containment problem is reformulated as an optimal control problem on the communication topology by constructing a performance cost function that incorporates both control inputs and tracking errors. Then, a novel identifier–actor–critic reinforcement learning (RL) architecture based on neural networks (NNs) is developed to solve the Hamilton–Jacobi–Bellman (HJB) equation online without requiring prior knowledge of system dynamics. In addition, an auxiliary system is designed to compensate for the negative effect of input…

• NN
  National Natural Science Foundation of China