A Novel Integral Terminal Non-Homogeneous Super-Twisting Sliding Mode Speed Control of PMSM in Machine Tools Based on Iterative Learning Disturbance Observer

This study presents a novel control strategy to address the problem of speed tracking control of permanent magnet synchronous motors (PMSM) for machines tools. It combines a P-type iterative learning disturbance observer and a superior integral terminal non-homogeneous super-twisting sliding mode controller. Firstly, the PMSM mathematical model is established with an unknown disturbance. Then, a P-type iterative learning disturbance observer is proposed to estimate the unknown disturbances of the system and compensate for them through feedforward compensation. This addresses the problem that both internal and external uncertainties can lead to the degradation of motor control performance. To improve the dynamic and steady-state performance of the speed control system, an improved integral terminal sliding mode controller is proposed, and the improved non-homogeneous super-twisting algorithm is used as the switching control law. Finally, the stability and convergence of the system are ultimately demonstrated by the Lyapunov theorem. It is demonstrated from simulation results that the control method can successfully reduce chattering while improving the robustness, speed tracking performance, and anti-interference capabilities of the system.