Hamiltonian-based minimum-energy trajectory planning and tracking control for a motor-table system: part II system identification and adaptive tracking control

Abstract

In this paper, the motor-table system is realized to plan the minimum input energy trajectory (MIET) based on Hamiltonian by minimum input energy control (MIEC) approach. In the motor-table system, the unknown parameters are identified by particle swarm optimization. We can identify the parameters experimentally and the MIEC methods are implemented to find the MIET. The adaptive tracking controller is proposed to track the MIET to overcome the nonlinear friction force and external disturbance. Moreover, trapezoidal trajectory and regulator control are compared with the MIET by the proposed adaptive tracking controller. Finally, the MIET based on the adaptive tracking controller can obtain the minimum energy control input and robustness performance for the motor-table system. The numerical simulations and experimental results are demonstrated the proposed strategy successfully.