An adaptive control strategy for computer-based manipulators

Abstract

This paper focuses on the study of an adaptive control method based on the perturbation equations in the vicinity of a desired trajectory. The highly coupled nonlinear dynamic equations of a manipulator are expanded in the vicinity of a preplanned joint trajectory to obtain the perturbation equations. These perturbation equations are then used to design a feed-back control law about the desired trajectory. The torques for the joint actuators consist of nominal torques computed from the Newton-Euler equations of motion and the variational torques computed from the perturbation equations. Since the parameters in the perturbation equations are unknown and also slowly time-varying, a recursive least square identification scheme is used to perform on-line parameter identification. The parameters of the perturbation equations and the feedback gains of the controller are updated and adjusted in each sampling period successively to obtain the necessary control effort. This adaptive control strategy reduces the manipulator control problem from a nonlinear control to controlling a linear control system about a desired trajectory. Computer simulation studies of a three-jointed PUMA robot arm are performed on a VAX-11/780 computer to illustrate the performance of this adaptive control strategy.