Multi-Agent Based Adaptive Consensus Control for Multiple Manipulators with Kinematic Uncertainties

Abstract

An adaptive control approach is proposed to deal with the multiple manipulators consensus problem based on the multi-agent theory. In the current multi-agent literature, agents were assumed to have determined models. However, the practical manipulator's kinematics contains uncertain parameters. By using the projection method, the adaptive updating law for uncertain kinematic parameters is derived. Then, the estimated manipulator Jacobian matrix can be obtained to design the decentralized controller. By the proposed controller, all the manipulators' end-effectors move towards the same configuration to achieve certain coordination tasks. In addition, performance of the control system is analyzed by the Lyapunov method, and the consensus error is proved to approach zero. Finally, the effectiveness of the proposed scheme is illustrated by simulations on a multiple PUMA 560 robots system.