Nonlinear Control of the Permanent Magnet Synchronous Motor PMSM using Backstepping Method

This paper presents a nonlinear control of (PMSM) using backstepping. We will study the different performances and robustness of each type of control, by introducing a new Lyapunov function candidate with a large possibility of parameter choice. Simulation results clearly show that the speed and current tracking errors asymptotically converge to zeros. Compared with neural networks control schemes, we do not require the unknown parameters to be linear parametrizable. No regression matrices are needed, so no preliminary dynamical analysis is needed.