Decentralized Cooperative Control for Multi-Reconfigurable Manipulator Based on Adaptive Dynamic Programing

This paper proposes a decentralized cooperative control for multi-reconfigurable manipulator (MRM) based on Adaptive Dynamic Programing (ADP). The control method can achieve both motion path tracking and control the force between the manipulator and the controlled object. The dynamic model of reconfigurable manipulator and controlled object is established using the Newton-Euler algorithm and load distribution. When facing unknown terms in the model, radial basis function neural network (RBFNN) is used for approximation. By taking advantage of the ADP algorithm to obtain the optimal control strategy. The closed-loop MRM system is proved to be stable by using the Lyapunov theory. Finally, the effectiveness of the control method is verified through numerical simulation.