Decentralized adaptive control of robotic manipulators†

摘要

Abstract We develop a self-tuning-type adaptive control for robotic manipulators with six joints, and analyse the stability of the control system. In order to reduce the computational effort for obtaining the control input in real time, a decentralized adaptive control system is designed in which each joint of the manipulator is regarded as a subsystem and controlled independently in parallel. In this control system we regard the interaction among the multiple joints as an unknown input in each subsystem. The influence of the interaction on the stability of the overall control system is analysed using a Lyapunov function. The theoretical result obtained is that the control system is always stable in the sense that the error between the output of the adaptive predictor and the real output (angular velocity of each joint) will not exceed the amount of interaction. This result is verified by some simulation studies.