Adaptive Dynamic Programming-Based Distributed Coordinated Control for Dual-Arm Reconfigurable Manipulators

In this paper, a distributed coordinated control method of dual-arm reconfigurable manipulators based on adaptive dynamic programming is proposed. Through kinematic analysis, the dynamic models of the reconfigurable manipulators and the grasped object are established, respectively. According to the load distribution method, the motion induction force is effectively distributed on each arm. Then, the dynamic model of a single reconfigurable manipulator is obtained. The performance index function is defined to reflect the joint position tracking error and internal force tracking error. The neural network is utilized to approximate the performance index function to obtain the optimal control strategy through the Policy Iteration (PI) algorithm. Thus, a distributed optimal coordinated controller is acquired. The tracking error of the manipulator system is proved be ultimately uniformly bounded (UUB) through Lyapunov's stability. Finally, the effectiveness of the developed control method is verified by simulations.