Adaptive Tracking Control of the Minimum-Energy Trajectory for a Mechatronic Motor-Table System

Abstract

In this paper, a mechatronic motor-table system is realized to plan the minimum input electrical energy trajectory based on the Hamiltonian function. In this system, unknown parameters are identified by particle swarm optimization, and an adaptive tracking controller is designed to track the minimum input electrical energy trajectory to overcome the nonlinear friction and external disturbance. Moreover, trapezoidal trajectory and regulator control are compared with the minimum input electrical energy trajectory by an adaptive tracking controller. Finally, it can be concluded that the minimum input electrical energy trajectory based on the adaptive tracking controller can obtain the minimum input electrical energy and robustness performance for the mechatronic motor-table system. Numerical simulations and experimental results demonstrate the adaptive tracking control strategy successfully in the minimum-energy trajectory.