Modeling and analysis of field-oriented control based permanent magnet synchronous motor drive system using fuzzy logic controller with speed response improvement

The permanent magnet synchronous motor (PMSM) acts as an electrical motor mainly used in many diverse applications. The controlling of the PMSM drive is necessary due to frequent usage in various systems. The conventional proportional-integral-derivative (PID) controller’s drawbacks are overcome with fuzzy logic controller (FLC) and adopted in the PMSM drive system. In this manuscript, an efficient field-oriented control (FOC) based PMSM drive system using a fuzzy logic controller (FLC) is modeled to improve the speed and torque response of the PMSM. The PMSM drive system is modeled using abc to αβ and αβ to abc transformation, 2-level space vector pulse width modulation (SVPWM), AC to DC rectifier with an inverter, followed by PMSM drive, proportional integral (PI) controller along with FLC. The FLC’s improved fuzzy rule set is adopted to provide faster speed response, less % overshoot time, and minimal steady-state error of the PMSM drive system. The simulation results of speed response, torque response, speed error, and phase currents are analyzed. The FLC-based PMSM drive is compared with the conventional PID-based PMSM drive system with better improvements in performance metrics

Modeling and simulation of PMSM control system based on SVPWM

The paper introduces the basic principle of space vector pulse width modulation simply and expatiates a method for implementing space vector pulse width modulation in detail based on MATLAB/SIMULINK, designs modeling and simulation of AC servo system with PMSM (Permanent Magnet Synchronous Motor), the simulation results show that the model is effective, and the method provides a base for both software and hardware design of an actual PMSM

Design and Control of Electrical Motor Drives

Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito

Sensorless Speed Drives Of Permanent Magnet Syhchronous Motor Using Model Reference Adaptive Control

In high performance drives, speed and torque controls of permanent magnet synchronous motors are usually attained by the application of position and speed sensors. However, speed and position sensors require the additional mounting space, reduce the reliability in harsh environments and increase the cost of the motor. Therefore, many studies have been carried out and reported to eliminate the speed and position sensors such as back electromotive force, signal injection, and others. However, these techniques have the drawbacks such as sensitive to machine parameter and others. The research focuses on investigation an evaluation of the sensorless speed control of surface mounted permanent magnet synchronous motor (SMPMSM) drives controlled by PI speed controller based on MRAC combined with V-I model and reactive power model. A Model Reference Adaptive Control (MRAC) has been chosen in this research based on its simplicity, good stability, and requires less computation. The SMPMSM is controlled using the principle of rotor flux orientation. Current control is performed in rotor reference frame based on SVPWM. The drives is simulated using SIMULINK/ MATLAB and the hardware implementation is based on dSPACE (DS1103). PI speed and current controllers are at first designed and the controller parameters are manually tuned to obtain steady state stability. A detailed investigation of the varies operating points; different speed command, forward-reverse speed operation, inertia variation and different speed command profiles. The overshoot/undershoot, settling time, and rise time of the speed response are used to evaluate the controller and speed estimation methods. The simulation and experimental with MRAC combined with V-I model speed estimation method results have proved that the drives is robust to the inertia variation, load rejection properties, speed variation and different initial speed profiles. Finally, the experimental investigation in MRAC combined with V-I model speed estimation method is performed in order to confirm the theoretical findings

High performance position control for permanent magnet synchronous drives

In the design and test of electric drive control systems, computer simulations provide a useful way to verify the correctness and efficiency of various schemes and control algorithms before the final system is actually constructed, therefore, development time and associated costs are reduced. Nevertheless, the transition from the simulation stage to the actual implementation has to be as straightforward as possible. This document presents the design and implementation of a position control system for permanent magnet synchronous drives, including a review and comparison of various related works about non-linear control systems applied to this type of machine. The overall electric drive control system is simulated and tested in Proteus VSM software which is able to simulate the interaction between the firmware running on a microcontroller and analogue circuits connected to it. The dsPIC33FJ32MC204 is used as the target processor to implement the control algorithms. The electric drive model is developed using elements existing in the Proteus VSM library. As in any high performance electric drive system, field oriented control is applied to achieve accurate torque control. The complete control system is distributed in three control loops, namely torque, speed and position. A standard PID control system, and a hybrid control system based on fuzzy logic are implemented and tested. The natural variation of motor parameters, such as winding resistance and magnetic flux are also simulated. Comparisons between the two control schemes are carried out for speed and position using different error measurements, such as, integral square error, integral absolute error and root mean squared error. Comparison results show a superior performance of the hybrid fuzzy-logic-based controller when coping with parameter variations, and by reducing torque ripple, but the results are reversed when periodical torque disturbances are present. Finally, the speed controllers are implemented and evaluated physically in a testbed based on a brushless DC motor, with the control algorithms implemented on a dsPIC30F2010. The comparisons carried out for the speed controllers are consistent for both simulation and physical implementation

Current derivative estimation for sensorless motor drives

The work presented in this thesis aims to improve the performance of the Fundamental PWM sensorless control technique by proposing a new way to estimate current derivatives in the presence of high frequency oscillations. The Fundamental PWM technique offers performance across the entire speed range (including zero speed). The method requires current derivative measurements when certain PWM (Pulse Width Modulation) active and null vectors are applied to the machine. However the switching action of the active devices in the inverter and the associated large dv/dt result in current and current derivative waveforms being affected by high frequency oscillations which prevent accurate measurement of the current derivative. Other approaches have allowed these oscillations to decay before attempting to take a derivative measurement. This requires that the PWM vectors are applied to the machine for a time sufficient to allow the oscillations to decay and a derivative measurement to be made (the minimum pulse width). On some occasions this time is longer than the time a vector would have normally been applied for (for example when operating at low speed) and the vectors must be extended and later compensated. Vector extension introduces undesirable current distortion, audible noise, torque ripple and vibration. In this thesis the high frequency oscillations and their sources are investigated and a method of using Artificial Neural Networks to estimate current derivatives using only a short window of the transient current response is proposed. The method is able to estimate the derivative directly from phase current measurements affected by high frequency oscillations and thus allows a reduction in the minimum pulse width to be achieved (since it is no longer necessary to wait for the oscillations to fully decay) without the need for dedicated current derivative sensors. The performance of the technique is validated with experimental results

High performance disturbance observer based control system design for permanent magnet synchronous AC machine applications

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonAn electrical machine is one of the main workforces in different industries and serves them in various applications. Machine drive control design involves many technical issues for efficient and robust exploitation. Over several decades, Permanent Magnet Synchronous Motor (PMSM) is getting preferred for industrial applications over its counterpart Squirrel Cage Induction Motor (SCIM) drive, because of their higher efficiency, power density, and higher torque to inertia ratio. In the prospective that PMSM drives are considered the drives of the future, there are still technical challenges and issues related to PMSM control. Many studies have been devoted to PMSM control in the past, but there are still some open research areas that bring worldwide researchers’ interests back to PMSM drive control. One of the approaches that may facilitate better performance, higher efficiency, and robust and reliable work of the control system is the disturbance observer-based control (DOBC) with linear and nonlinear output feedback control for PM synchronous machine applications. DOBC is adopted due to its ability to reject external and internal disturbances with improving tracking performance in the variable speed wind energy conversion system (WECS) to maximize power extraction. The high order disturbance observer (HODO) is utilized to estimate the aerodynamic torque-based wind speed without the use of a traditional anemometer, which reduces the overall cost and improves the reliability of the whole system. Also, this method has been designed to improve the angular shaft speed tracking of the PMSM system under load torque disturbance and speed variations. The model-based linear and nonlinear feedback control are used in the proposed control systems. The sliding mode control (SMC) with switching output feedback control law and integral SMC with linear feedback and state-dependent Riccati equation (SDRE) based approaches have been designed for the systems. The SDRE control accounts for the nonlinear multivariable structure of the WECS and is approximated with Taylor series expansion terms. The chattering inherited from SMC is eliminated by the continuous approximation technique. The sliding mode is guaranteed by eliminating the reaching mode in the proposed integral SMC. The model-free cascaded linear feedback control system based on the proportional-integral (PI) controllers use a back-calculation algorithm anti-windup scheme. The proposed speed controllers are synthesized with HODO to compensate for the external disturbance, model uncertainty, noise, and modelling errors. Moreover, servomechanism-based SDRE control, a near-optimal control system is designed to suppress the model uncertainty and noise without the use of disturbance observers. The proposed control systems for PMSM speed regulation have demonstrated a significant improvement in the angular shaft speed-tracking performance at the transients. Their performances have been tested under speed, load torque variations, and model uncertainty. For example, HODO-based SMC with switching output feedback control law (SOFCL) has demonstrated improvement by more than 78% than the PI-PI control system of the PMSM. The performance of the HODOs-based Integral SMC with SDRE nonlinear feedback is improved by 80.5% under external disturbance, model uncertainty, and noise than Integral SMC with linear feedback in the WECS. The HODO-based SDRE control with servomechanism has shown an 80.2% improvement of mean absolute percentage error under disturbances than Integral SMC with linear feedback in the WECS. The PMSM speed tracking performance of the proposed HODO-based discrete-time PI-PI control system with back-calculation algorithm anti-windup scheme is improved by 87.29% and 90.2% in the speed commands and load torque disturbance variations scenarios respectively. The simulations for testing the proposed control system of the PMSM system and WECS have been implemented in Matlab/Simulink environment. The PMSM speed control experimental results have been obtained with Lucas-Nuelle DSP-based rapid control prototyping kit.Center for International Program “Bolashak” of the Ministry of Education and Science Republic of Kazakhsta

Current derivative estimation for sensorless motor drives

The work presented in this thesis aims to improve the performance of the Fundamental PWM sensorless control technique by proposing a new way to estimate current derivatives in the presence of high frequency oscillations. The Fundamental PWM technique offers performance across the entire speed range (including zero speed). The method requires current derivative measurements when certain PWM (Pulse Width Modulation) active and null vectors are applied to the machine. However the switching action of the active devices in the inverter and the associated large dv/dt result in current and current derivative waveforms being affected by high frequency oscillations which prevent accurate measurement of the current derivative. Other approaches have allowed these oscillations to decay before attempting to take a derivative measurement. This requires that the PWM vectors are applied to the machine for a time sufficient to allow the oscillations to decay and a derivative measurement to be made (the minimum pulse width). On some occasions this time is longer than the time a vector would have normally been applied for (for example when operating at low speed) and the vectors must be extended and later compensated. Vector extension introduces undesirable current distortion, audible noise, torque ripple and vibration. In this thesis the high frequency oscillations and their sources are investigated and a method of using Artificial Neural Networks to estimate current derivatives using only a short window of the transient current response is proposed. The method is able to estimate the derivative directly from phase current measurements affected by high frequency oscillations and thus allows a reduction in the minimum pulse width to be achieved (since it is no longer necessary to wait for the oscillations to fully decay) without the need for dedicated current derivative sensors. The performance of the technique is validated with experimental results

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