Practical tracking control of industrial robots using optimal inverse dynamics design

In this paper, an optimal technique for motion control of industrial robots is proposed. Robot dynamics is considered as a multivariable nonlinear case. Moreover, the practical situation including disturbances and actuators' saturation is taken into account. Thus, using sequential quadratic programming optimization (SQP), an optimal technique based on the inverse dynamics is proposed. Satisfying the condition for the dynamics to be used by feedback linearization, the saturation phenomenon is approximated by an inverse tangent function. The simulation results for a 2-DOF direct-drive robot arm excellently justify the problem of tracking of different trajectories in comparison with the conventional LQG/LTR method.