# High-Performance Speed Control of PMSM Using Fuzzy Sliding Mode with Load Torque Observer
###### Abstract  
To enhance the speed control performance of the permanent magnet synchronous motor (PMSM) servo system, an improved sliding mode control method integrating a torque observer is presented. The current loop uses current feedback decoupling PID control, and the speed loop applies sliding mode control. In comparison to previous work in hybrid SMC using fuzzy logic and torque observers, this p proposes a hyperbolic tangent function in replacement of the signum function to solve the conflict between rapidity and chattering in the traditional exponential reaching law, and fuzzy and segmental self-tuning rules adjust relevant switching terms to reduce chattering and improve the sliding mode arrival process. A load torque observer is designed to enhance the system's anti-interference ability by compensating the observed load torque to the current loop input. Simulation results show that compared with traditional sliding mode control with a load torque observer (SMC + LO), PID control with a load torque observer (PID + LO), and Active Disturbance Rejection Control (ADRC), the proposed strategy can track the desired speed in 0.032 s, has a dynamic deceleration of 2.7 r/min during sudden load increases, and has a recovery time of 0.011 s, while the others have relatively inferior performance. Finally, the model experiment is carried out, and the results of the experiment are basically consistent with the simulation results. Simulation and experimental results confirm the superiority of the proposed control strategy in improving the system's comprehensive performance. sliding mode control; torque observer; permanent magnet synchronous motor; fuzzy self-tuning; chattering 20  
performance. The root cause of this problem is related to the symmetry of the switching of the system's control variables. In [7], the state of the system is introduced to form the variable exponential power law, which reduces chattering and accelerates the state approaching speed, but the design process and the parameter adjustment are all complex. In [8], an approach law is designed by using fractional integral symbolic function to reduce chattering and increase response speed, but there is a steady-state error. In [9], a fast power law with a variable exponent is proposed to decrease chattering phenomenon. However, more parameters have to be adjusted. In [10], a chattering-free finite-time approximation law with input constraints is designed, and unfortunately its rapidity is limited. In [11], the paper proposes a fuzzy sliding mode switching controller based on adaptive law, which approximates the switching term of sliding mode control law by fuzzy algorithm to reduce system chattering. In [12], in order to ensure global robustness and reduce chattering, a full-range fractional-order integral sliding mode surface is proposed, but the controller has many parameters. In [13], an adaptive integral sliding mode is used to reduce chattering and steady-state error, but large initial error will lead to large overshoot and long adjustment time. In [14], to reduce chattering and realize finite-time speed control, a generalized super-twisting sliding mode algorithm is proposed, but steady-state analysis is complex, and the control parameters are difficult to adjust. In addition, the load is also one of the main reasons that affect the system performance. The common method to restrain the influence of load disturbance is to measure torque directly or indirectly and then compensate it. The direct measurement method is not only costly but also high for mechanical sensors, and the indirect measurement method is low in cost and good in reliability [15]. In [16], a Kalman filter model is established to accurately observe the load torque, but the computation is large, and the parameter tuning is difficult. In [17], a torque compensation strategy based on an extended state observer is proposed. However, prior knowledge is required to determine the nominal parameters.