Stochastic adaptive control for robotic manipulator with control input constraints

An adaptive controller is synthesized to control the motion of an n-degrees of freedom direct drive robotic manipulator. The design of the adaptive controller is based on minimum variance control with model reference which depends on the nominal values of the position and angular velocity of the manipulator joints. The parameters of the adaptive controller are estimated on line using the least squares algorithm. In the controller the end effector velocity of the manipulator is monitored in a servo loop, and the position and angular velocity of each joint of the manipulator are compelled to track their nominal values. This controller comprises an n-input vector for the actuator torque, and a 6-output vector for the linear and angular end effector velocities. The actuators of the direct drive manipulator are taken to be permanent magnet motors. Their dynamics and constraints are considered in the proposed controller. Digital computer simulations are made to demonstrate the tracking performance, robustness and applicability of the adaptive controller