High performance position control of 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, reducing development time and associated costs. Nevertheless, the transition from the simulation stage to the actual implementation has to be as straightforward as possible. This paper presents the design and implementation of a position control system for permanent magnet synchronous drives using the dsPIC33FJ32MC204 microcontroller as the target processor to implement the control algorithms. The overall system is simulated and tested in Proteus VSM software which is able to simulate the interaction between the firmware running on the microcontroller and the analogue circuits connected to it. The electric drive model is developed using elements present in the Proteus VSM library. As in any high-performance AC electric drive system, field oriented control is applied. 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 control 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 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.N/

Self organizing fuzzy sliding mode controller for the position control of a permanent magnet synchronous motor drive

AbstractIn this paper, a self organizing fuzzy sliding mode controller (SOFSMC) which emulates the fuzzy controller with gain auto-tuning is proposed for a permanent magnet synchronous motor (PMSM) drive. The proposed controller is used for the position control of the PMSM drive. The performance and robustness of the control system is tested for nonlinear motor load torque disturbance and parameter variations. It has a novel gain self organizing strategy in response to the transient or tracking responses requirement. To illustrate the performance of the proposed controller, the simulation studies are presented separately for the SOFSMC and the fuzzy controller with gain auto-tuning. The results are compared with each other and discussed in detail. Simulation results showing the effectiveness of the proposed control system are confirmed under the different position changes

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

A New Synergetic Scheme Control of Electric Vehicle Propelled by Six-phase Permanent Magnet Synchronous Motor

Electric Vehicles (EVs) are a promising al- ternative to conventional vehicles powered by internal combustion motors, offering the possibility of reduc- ing CO2, pollutants, and noise emissions. As known, the control of such an electric vehicle takes into ac- count several phenomena governing its behavior, which is a complicated problem because of the non-linearities, unmeasured disturbance, and parameters uncertainty of this system. This problem is one of the important challenges facing controller designers. Various control techniques have been proposed to enhance Ev’s perfor- mance. On this basis, in this research, a new synergetic scheme of electric vehicles propelled by Six-Phase Per- manent Magnet Synchronous Motor (PMSMs) is de- veloped. The synthesis of the proposed Synergetic Con- troller (SC) is based on the selection of four-manifolds of stator current of PMSMs. The SC provides fast response, asymptotic stability of the closed-loop sys- tem in wide range operating condition, and decrease the size of modeled system. Also, the principal fea- ture of SC is that it supports parameters variation. Furthermore, to illustrate the improvements and the performances of the proposed controller, a compari- son study between various nonlinear controllers such as Integral Action in Sliding Mode (ISMC), Super Twist- ing Sliding Mode (STSM), using a dynamic model of the lightweight vehicle under New European Driv- ing Cycle (NEDC) was done. The obtained simula- tion results under several operating conditions show the efficiency and superiority of the proposed control compared with nonlinear controllers; also, it demon- strates the feasibility of the proposed control approach for real system

Fractional order sliding mode controller based on supervised machine learning techniques for speed control of PMSM

Tracking the speed and current in permanent magnet synchronous motors (PMSMs) for industrial applications is challenging due to various external and internal disturbances such as parameter variations, unmodelled dynamics, and external load disturbances. Inaccurate tracking of speed and current results in severe system deterioration and overheating. Therefore, the design of the controller for a PMSM is essential to ensure the system can operate efficiently under conditions of parametric uncertainties and significant variations. The present work proposes a PMSM speed controller using machine learning (ML) techniques for quick response and insensitivity to parameter changes and disturbances. The proposed ML controller is designed by learning fractional-order sliding mode control (FOSMC) controller behavior. The primary purpose of using ML in FOSMC is to avoid the self-tuning of the parameters and ensure the speed reaches the reference value in finite time with faster convergence and better tracking precision. Furthermore, the ML model does not require the mathematical model of the speed controller. In this work, several ML models are empirically evaluated on their estimation accuracy for speed tracking, namely ordinary least squares, passive-aggressive regression, random forest, and support vector machine. Finally, the proposed controller is implemented on a real-time hardware-in-the-loop (HIL) simulation platform from PLECS Inc. Comparative simulation and experimental results are presented and discussed. It is shown from the comparative study that the proposed FOSMC based on ML outperformed the traditional sliding mode control (SMC), which is more commonly used in industry in terms of tracking speed and accuracy

A Nonlinear Sliding Mode Controller for IPMSM Drives with an Adaptive Gain Tuning Rule

This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC metho

Application of Sliding Mode Controller and Linear Active Disturbance Rejection Controller to a PMSM Speed System

Permanent magnet synchronous motor (PMSM) is a popular electric machine in industry for its small volume, high electromagnetic torque, high reliability and low cost. It is broadly used in automobiles and aircrafts. However, PMSM has its inherent problems of nonlinearity and coupling, which are challenges for control systems design. In addition, the external disturbances such as load variation and noises could degrade the systems performance. Both sliding mode control (SMC) and active disturbance rejection control (ADRC) are robust against disturbances. They can also compensate the nonlinearity and couplings of the PMSM. Therefore, in this thesis, we apply both SMC and ADRC to a PMSM speed system. Our control goal is to drive the speed outputs of the PMSM speed system to reference signals in the presences of nonlinearity, disturbance, and parameter variations. Simulation results verify the effectiveness of SMC and ADRC on the speed control for PMSM systems in spite of the presences of external disturbance and internal system uncertaintie

A Nonlinear Sliding Mode Controller for IPMSM Drives with an Adaptive Gain Tuning Rule

This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC metho

Conformable Fractional Order PI Controller Design and Optimization for Permanent Magnet Synchronous Motor Speed Tracking System

The use of permanent magnet synchronous motor (PMSM) is increasing rapidly to meet the need to increase efficiency in variable speed drive systems used in the industry, in recent years. This paper aims to improve the speed control performance of the PMSM based systems. To achieve this, a PMSM speed controller is designed based on the conformable fractional order proportional integral (CFOPI) method. CFOPI controller coefficients kp, ki and γ are optimized using response surface method (RSM). To validate the success of the proposed scheme, the CFOPI controller and the integer order PI (IOPI) controller are tested under the same simulation model and the results are compared. The proposed method grants robust performance with less computational load then the classical fractional order controllers for variable referenced PMSM speed tracking systems. The CFOPI controller can be applied easily for industrial variable speed drive systems which is using PMSM to improve the performance and stability of the systems

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