The analysis of different techniques for speed control of permanent magnet synchronous motor

U radu se predstavljaju tehnike reguliranja brzine primjenom proporcionalnog integrala (PI), derivacije proporcionalnog integrala i fuzzy logike u pogonu sinkronog motora s permanentnim magnetima. PI i PID regulatori zahtijevaju precizni linearni matematički model sustava. S druge strane, FL zahtijeva lingvistički opis sustava. Analizirana je dinamička reakcija PMSMa na regulatore pri različitim opterećenjima. Uspoređena je učinkovitost reguliranja fuzzy logikom i uobičajenim načinima pomoću PI i PID. FL regulatori su reagirali bolje od uobičajenih tehnika pri prelaznim uvjetima opterećenja te postigli bržu regulaciju.This paper presents the use of proportional integral (PI), proportional integral derivative (PID) and fuzzy logic (FL) speed controller techniques in the permanent magnet synchronous motor (PMSM) drive. PI and PID controllers require precise linear mathematical model of the system. On the other hand, FL needs linguistic description of the system. The dynamic response of PMSM with the controllers was studied under different load disturbances. The effectiveness of the fuzzy logic controller was compared with the conventional PI and PID controllers. The FL controller responded better than conventional techniques under transient load conditions and also achieved faster settling response

Sensorless Speed Control of Permanent Magnet Synchronous Motors by Neural Network Algorithm

The sliding mode control has the merits with respect to the variation of the disturbance and robustness. In this paper, the sensorless sliding-mode observer with least mean squared error approach for permanent magnet synchronous motor (PMSM) to detect the rotor position by counter electromotive force and then compute motor speed is designed and implemented. In addition, the neural network control is also used to compensate the PI gain tuning to increase the speed accuracy without regarding the errors of the current measurement and motor noise. In this paper, a digital signal processor TMS320F2812 utilizes its high-speed ADC module to get current feedback information and thus to estimate the rotor position and takes advantage of the built-in modules to achieve SVPWM current control so that the senseless speed control will be accomplished. The correctness and effectiveness of the proposed control system will be verified from the experimental results

Enhanced Speed and Current Control of PMSM Drives by Perfect Tracking Algorithms

Abstract-Speed and current closed loops control represent the heart of any advanced AC servo drive. These inner loops usually feature high-dynamic feedback control, with possible axes decoupling and a straight feedforward action of the backelectromotive force (back-EMF). More sophisticated techniques as single-rate or multi-rate control could be exploited for both speed and current closed loops, and their performances compared to that of the classic cascade feedback controllers. This represents the goal of the present work, focusing on permanent magnet synchronous motor (PMSM) drives

Nonlinear disturbance observer-based control for multi-input multi-output nonlinear systems subject to mismatching condition

For a multi-input multi-output (MIMO) nonlinear system, the existing disturbance observer-based control (DOBC) only provides solutions to those whose disturbance relative degree (DRD) is higher than or equal to its input relative degree. By designing a novel disturbance compensation gain matrix, a generalised nonlinear DOBC method is proposed in this article to solve the disturbance attenuation problem of the MIMO nonlinear system with arbitrary DRD. It is shown that the disturbances are able to be removed from the output channels by the proposed method with appropriately chosen control parameters. The property of nominal performance recovery, which is the major merit of the DOBCs, is retained with the proposed method. The feasibility and effectiveness of the proposed method are demonstrated by simulation studies of both the numerical and application examples

ADRC and Feedforward Hybrid Control System of PMSM

The permanent-magnet synchronous motor (PMSM) is a complex controlled object that is difficult to drive and control. In this study, the vector control strategy is adopted to drive the PMSM. The active disturbance rejection controller is used to achieve the closed-loop control of PMSM, which simplifies the computational complexity. A load torque observer and feedforward compensation component are designed to overcome the PMSM speed fluctuation of the load disturbance. An experimental system based on the DSP board is designed to test the controller performance. The results validate the control algorithm

Fixed Switching Period Discrete-Time Sliding Mode Current Control of a PMSM

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksA fixed switching period sliding mode control (SMC) for Permanent Magnet Synchronous Machines (PMSMs) is presented. The aim of the paper is to design a SMC that improves the traditional PI based Field Oriented Control (FOC) transient response, as well as to reduce the switching frequency variations of the Direct Torque Control (DTC). Such SMC requires a decoupling method of the control actions, which also brings constant switching functions slopes. These constant slopes allow to calculate the required hysteresis band value to control the switching frequency. The digital implementation degrades the performance of the hysteresis comparator and as a consequence, the previously calculated band becomes inaccurate to regulate the switching frequency. In order to recover the analogue hysteresis band comparator performance, a predictive algorithm is proposed. Finally, a set of experimental results with constant switching frequency during a torque reversal and speed control tests are provided.Peer ReviewedPostprint (author's final draft

Design and Implementation of Recursive Model Predictive Control for Permanent Magnet Synchronous Motor Drives

In order to control the permanent-magnet synchronous motor system (PMSM) with different disturbances and nonlinearity, an improved current control algorithm for the PMSM systems using recursive model predictive control (RMPC) is developed in this paper. As the conventional MPC has to be computed online, its iterative computational procedure needs long computing time. To enhance computational speed, a recursive method based on recursive Levenberg-Marquardt algorithm (RLMA) and iterative learning control (ILC) is introduced to solve the learning issue in MPC. RMPC is able to significantly decrease the computation cost of traditional MPC in the PMSM system. The effectiveness of the proposed algorithm has been verified by simulation and experimental results

Nonlinear disturbance observer-based control for multi-input multi-output nonlinear systems subject to mismatching condition

This article was published in the serial International Journal of Control [© Taylor and Francis] and the definitive version is available at: http://www.tandfonline.com/doi/abs/10.1080/00207179.2012.675520For a multi-input multi-output (MIMO) nonlinear system, the existing disturbance observer-based control (DOBC) only provides solutions to those whose disturbance relative degree (DRD) is higher than or equal to its input relative degree. By designing a novel disturbance compensation gain matrix, a generalised nonlinear DOBC method is proposed in this article to solve the disturbance attenuation problem of the MIMO nonlinear system with arbitrary DRD. It is shown that the disturbances are able to be removed from the output channels by the proposed method with appropriately chosen control parameters. The property of nominal performance recovery, which is the major merit of the DOBCs, is retained with the proposed method. The feasibility and effectiveness of the proposed method are demonstrated by simulation studies of both the numerical and application examples

Adaptive Two-Stage Extended Kalman Filter Theory in Application of Sensorless Control for Permanent Magnet Synchronous Motor

Extended Kalman filters (EKF) have been widely used for sensorless field oriented control (FOC) in permanent magnet synchronous motor (PMSM). The first key problem associated with EKF is that the estimator requires all the plant dynamics and noise processes are exactly known. To compensate inaccurate model information and improve tracking ability, adaptive fading extended Kalman filtering algorithms have been proposed for the nonlinear system. The second key problem is that the EKF suffers from computational burden and numerical problems when state dimension is large. The two-stage extended Kalman filter (TSEKF) with respect to this problem has been extensively studied in the past. Combining the advantages of both AFEKF and TSEKF, this paper presents an adaptive two-stage extended Kalman filter (ATEKF) for closed-loop position and speed estimation of a PMSM to achieve sensorless operation. Experimental results demonstrate that the proposed ATEKF algorithm for PMSMs has strong robustness against model uncertainties and very good real-time state tracking ability

Adaptive Two-Stage Extended Kalman Filter Theory in Application of Sensorless Control for Permanent Magnet Synchronous Motor

Extended Kalman filters (EKF) have been widely used for sensorless field oriented control (FOC) in permanent magnet synchronous motor (PMSM). The first key problem associated with EKF is that the estimator requires all the plant dynamics and noise processes are exactly known. To compensate inaccurate model information and improve tracking ability, adaptive fading extended Kalman filtering algorithms have been proposed for the nonlinear system. The second key problem is that the EKF suffers from computational burden and numerical problems when state dimension is large. The two-stage extended Kalman filter (TSEKF) with respect to this problem has been extensively studied in the past. Combining the advantages of both AFEKF and TSEKF, this paper presents an adaptive two-stage extended Kalman filter (ATEKF) for closed-loop position and speed estimation of a PMSM to achieve sensorless operation. Experimental results demonstrate that the proposed ATEKF algorithm for PMSMs has strong robustness against model uncertainties and very good real-time state tracking ability