Abstract
In the case of using a Permanent Magnet Synchronous Motor (PMSM) linear model of limited-range parametric variations and of relatively low dynamic of the load torque, the Field Oriented Control (FOC) type strategy ensures good performance of the PMSM control. Therefore, when using a non-linear model of wide-range parametric variations and of high dynamic of the load torque, a backstepping-type controller is proposed, whose tuning parameters are optimized by using a Particle Swarm Optimization (PSO) method. By designing an Extended State Observer (ESO), which provides a good estimate of the PMSM rotor position and speed under uncertainty conditions and with a response time shorter than that of the backstepping-type controller, this observer can be incorporated into the PMSM sensorless control system. The superior performance of the proposed sensorless control system based on the backstepping-PSO-type controller and an ESO-type observer is demonstrated through numerical simulations. Given that the real-time implementation of the control algorithms and observers in an embedded system is a difficult task, consisting of several steps, it is presented after the numerical simulations, which can be assimilated into the Software-in-the-Loop (SIL) step, the Processor-in-the-Loop (PIL) intermediate step, and the Hardware-in-the-Loop (HIL) final step. A comparison between the backstepping-PSO-type controller and the PI-PSO-type controller is presented by means of the real-time implementation of these controllers and demonstrates the superiority of the backstepping-PSO-type controller.
Highlights
Permanent Magnet Synchronous Motor (PMSM) have increasing applicability due to their advantages such as superior performance, reliability, and the fact that they are compact and suitable for operating conditions.Thanks to its high-duty density and smaller dimensions, the PMSM has become the preferred solution for the control of speed and position in machine tools and robots
Based on the Field Oriented Control (FOC)-type classic control structure, under the conditions where even the optimization of the tuning parameters of the classic PI controller is performed by a PSOtype method, we note that the PMSM control system can ensure good performance only in the case of limited variations of the system parameters, and not in the case of high dynamics and sudden variations of the load torque
Based on the FOC-type classic control structure, under the conditions where even the optimization of the tuning parameters of the classic PI controller is performed by a Particle Swarm Optimization (PSO)-type method, we note that the PMSM control system can ensure good performance only in the case of limited variations of the system parameters, and not in the case of high dynamics and sudden variations of the load torque
Summary
PMSMs have increasing applicability due to their advantages such as superior performance, reliability, and the fact that they are compact and suitable for operating conditions. The FOC-type control strategy of the PMSM includes all the advantages deriving from the simplicity of using PI controllers, but inherently, the control performance is limited due to the non-linear PMSM model, the need to perform the control in a wide range and with a high-dynamic of speed and load torque, and due to the parametric uncertainties resulting, in particular, from the variation of the combined rotor-load moment of inertia [6,7]. Design of a backstepping-type controller, optimization of its tuning parameters using a PSO optimization method, and synthesis of an ESO-type observer to estimate the speed and position of the PMSM rotor and the load torque; Validation of the superior performance of the proposed sensorless PMSM control system through numerical simulations, based on the backstepping-PSO-type con-. Troller and ESO-type observer under the conditions of parametric variations and high-dynamic of the load torque; Presentation of all the steps for the real-time implementation in the embedded system, covering the SIL, PIL, and HIL steps.
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