Adaptive trajectory tracking control of a 6R serial manipulator

One of the main issues encountered in the industrial manipulator applications is the control problem. While the conventional PID control method still dominates the industry, it proves ineffective when some of the kinematic and inertial parameters of the system are uncertain. The aim of this study is to design a self-tuning PID computed torque controller for a 6R robot arm and investigate the effectiveness of the self-tuning adaptive method under such cases. To this end, the control strategy presented here is tested using a simulation environment written in GNU Octave programming language. The robot arm is simulated while it carries payloads with unknown inertial parameters and the results of the adaptive controller are compared with the conventional PID computed torque controller. Furthermore, all necessary system analyses and their formulations have been presented including kinematics, robot arm dynamics and trajectory planning. Results reveal that the self-tuning adaptive controller can successfully compensate the parametric uncertainties and sustain the system stability within the same error margin of the conventional PID control method when dynamic model includes heavy uncertainties.