Integral backstepping control for a PMSM drive using adaptive FNN uncertainty observer

An integral backstepping control system is proposed to control the rotor position of a permanent magnet synchronous motor (PMSM) drive using adaptive fuzzy neural network uncertainty observer (AFNNUO) in this paper. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMSM servo drive. Then, an integral backstepping approach is proposed to control the motion of PMSM drive system. With proposed integral backstepping control system, the rotor position of the PMSM 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 PMSM drive, an adaptive FNN uncertainty observer is proposed to estimate the required lumped uncertainty in integral backstepping control system. In addition, an on-line parameter training methodology, which is derived using the gradient descent method, is proposed to increase the learning capability of the FNN. The effectiveness of the proposed control scheme is verified by experimental results.