In this paper, we present the vector control of a permanent magnet synchronous machine (PMSM) by a PI regulator whose tracking performance; speed, stability, and precision are satisfactory. However, we can see the influence of the variation in the resistance and load torque on the behavior of the controlled system. we analyze the simulation results found and then we make an inventory of PI disadvantages. This work is modified with a novelty by introducing a new control law namely sliding mode and backstepping control law. Then we analyze the results found making a comparison to those of the PI regulator.
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.
In the industry, the permanent magnet synchronous motors are one of the most widely used motors and have superior performance compared to the other types of motors. The principal objective of this paper is to ameliorate the performance of PMSMs by implementing a robust non-linear backstepping control. The first part deals with the vector control of mechanical sensors using PI controller. In the second part, we shed the light on the non-linear backstepping control, using Lyapunov function, of PMSM from the point of view of stability and robustness. The results are validated by MALTAB/SIMULINK. The results obtained show the good stability and good dynamic of PMSM’s control by backstepping controller, also the PI is very sensitive to parameter’s machine variation compared with the backstepping controller.
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