Performance enhancement of PMSM using a hybridizing of nonlinear backstepping control and an optimized linear quadratic regulator

An important characteristic of permanent magnet synchronous machines is that they are extremely efficient due to the absence of rotor losses, such as in induction motors, and the use of permanent magnets for field excitation. This makes them a superb choice for applications involving motors and generators. In motor applications, key considerations revolve around speed, torque, and how machine parameters are affected by changes in ambient circumstances. Regrettably, using permanent magnet synchronous motor is influenced by all these aspects. This allows researchers to develop successful hybridization approaches combining different advanced controls to achieve optimal control mechanisms for these motors. This work presents a hybridization of nonlinear and optimum controls for optimal performance of permanent magnet synchronous motor under varying operating conditions by combining backstepping control and linear quadratic regulator control. By including the error as a state variable and applying the linear quadratic regulator technique to determine the control law, the steady-state error is reduced. The optimal linear quadratic regulator technique is defined by stabilizing and reducing oscillations in the permanent magnet while increasing system performance based on steady-state error. Meanwhile, the backstepping control helps maintain the regime's stability in the face of disturbances, which are represented by variations in load torque, speed, and motor parameters. A comparison study was performed to assess the efficacy of the suggested system against two contemporary control techniques: Exponential reaching law-sliding mode control and model predictive control. The findings indicate the superiority of the recommended method. All simulations were performed using MATLAB/SIMULINK.