Integral Backstepping Control for a PMLSM Using Adaptive RNNUO

Due to uncertainties exist in the applications of the a permanent magnet linear synchronous motor (PMLSM) servo drive which seriously influence the control performance, thus, an integral backstepping control system using adaptive recurrent neural network uncertainty observer (RNNUO) is proposed to increase the robustness of the PMLSM drive. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMLSM servo drive. Then, an integral backstepping approach is proposed to control the motion of PMLSM drive system. With proposed integral backstepping control system, the mover position of the PMLSM drive possesses the advantages of good transient control performance and robustness to uncertainties for the tracking of periodic reference trajectories. Moreover, to further increase the robustness of the PMLSM drive, an adaptive RNN uncertainty observer is proposed to estimate the required lumped uncertainty. The effectiveness of the proposed control scheme is verified by experimental results.