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

PSO BASED TAKAGI-SUGENO FUZZY PID CONTROLLER DESIGN FOR SPEED CONTROL OF PERMANENT MAGNET SYNCHRONOUS MOTOR

A permanent magnet synchronous motor (PMSM) is one kind of popular motor. They are utilized in industrial applications because their abilities included operation at a constant speed, no need for an excitation current, no rotor losses, and small size. In the following paper, a fuzzy evolutionary algorithm is combined with a proportional-integral-derivative (PID) controller to control the speed of a PMSM. In this structure, to overcome the PMSM challenges, including nonlinear nature, cross-coupling, air gap flux, and cogging torque in operation, a Takagi-Sugeno fuzzy logic-PID (TSFL-PID) controller is designed. Additionally, the particle swarm optimization (PSO) algorithm is developed to optimize the membership functions' parameters and rule bases of the fuzzy logic PID controller. For evaluating the proposed controller's performance, the genetic algorithm (GA), as another evolutionary algorithm, is incorporated into the fuzzy PID controller. The results of the speed control of PMSM are compared. The obtained results demonstrate that although both controllers have excellent performance; however, the PSO based TSFL-PID controller indicates more superiority

Literature Review of PID Controller based on Various Soft Computing Techniques

This paper profound the various soft computing techniques like fuzzy logic, genetic algorithm, ant colony optimization, particle swarm optimization used in controlling the parameters of PID Controller. Its widespread use and universal acceptability is allocated to its elementary operating algorithm, the relative ease with the controller effects can be adjusted, the broad range of applications where it has truly developed excellent control performances, and the familiarity with which it is deduced among researchers. In spite of its wide spread use, one of its short-comings is that there is no efficient tuning method for PID controller. Given this background, the main objective of this is to develop a tuning methodology that would be universally applicable to a range of well-liked process that occurs in the process control industry

Fuzzy logic based online adaptation of current and speed controllers for improved performance of IPMSM drive

Precise torque and speed control of electric motors is a key issue in industries for variable speed drives (VSD). Over the years the induction motors have been widely utilized in industries for VSD applications. However, induction motor has some significant drawbacks like low efficiency, lagging power factor, asynchronous speed, low torque density etc. Nowadays the interior permanent magnet synchronous motor (IPMSM) is becoming popular for high performance variable speed drive (HPVSD) due to its high torque-current ratio, large power-weight ratio, high efficiency, high power factor, low noise and robustness as compared to conventional induction and other ac motors. Smooth torque response, fast and precise speed response, quick recovery of torque and speed from any disturbance and parameter insensitivity, robustness in variable speed domain and maintenance free operations are the main concerns for HPVSD. This work proposes a closed loop vector control of an IPMSM drive incorporating two separate fuzzy logic controllers (FLCs). Among them one FLC is designed. to minimize the developed torque ripple by varying online the hysteresis band of the PWM current controller. Another Sugeno type FLC is used to tune the gains of a proportional-integral (PI) controller where the PI controller actually serves as the primary speed controller. Thus, the limitations of traditional PI controllers will be avoided and the performance of the drive system can be improved. A flux controller is also incorporated in such a way that both torque and flux of the motor can be controlled while maintaining current and voltage constraints. The flux controller is designed based on maximum-torque- per-ampere (MTPA) operation below the rated speed and flux weakening operation above the rated speed. Thus, the proposed drive extends the operating speed limits for the motor and enables the effective use of the reluctance torque. In order to verify the performance of the proposed IPMSM drive, first a simulation model is developed using Matlab/Simulink. Then the complete IPMSM drive has been implemented in real-time using digital signal processor (DSP) controller board DS1104 for a laboratory 5 HP motor. The effectiveness of the proposed drive is verified both in simulation and experiment at different operating conditions. In this regard, a performance comparison of the proposed FLC based tuned PI and adapted hysteresis controllers based drive with the conventional PI and fixed bandwidth hysteresis controllers based drive is provided. These comparison results demonstrate the better dynamic response in torque and speed for the proposed IPMSM drive over a wide speed range

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

High-Performance Tracking for Piezoelectric Actuators Using Super-Twisting Algorithm Based on Artificial Neural Networks

Piezoelectric actuators (PEA) are frequently employed in applications where nano-Micr-odisplacement is required because of their high-precision performance. However, the positioning is affected substantially by the hysteresis which resembles in an nonlinear effect. In addition, hysteresis mathematical models own deficiencies that can influence on the reference following performance. The objective of this study was to enhance the tracking accuracy of a commercial PEA stack actuator with the implementation of a novel approach which consists in the use of a Super-Twisting Algorithm (STA) combined with artificial neural networks (ANN). A Lyapunov stability proof is bestowed to explain the theoretical solution. Experimental results of the proposed method were compared with a proportional-integral-derivative (PID) controller. The outcomes in a real PEA reported that the novel structure is stable as it was proved theoretically, and the experiments provided a significant error reduction in contrast with the PID.This research was funded by Basque Government and UPV/EHU projects

Development and implementation of various speed controllers for wide speed range operation of IPMSM drive / by Md Muminul Islam Chy.

Despite many advantageous features of interior permanent magnet synchronous motor (IPMSM), the precise speed control of an IPMSM drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinearity present in the electromagnetic developed torque due to magnetic saturation of the rotor core particularly, at high speeds (above rated speed). Fast and accurate response, quick recovery of speed from any disturbances and insensitivity to parameter variations are some of the important characteristics of high performance drive system used in robotics, rolling mills, traction and spindle drives. The conventional controllers such as PI, PID are sensitive to plant parameter variations and load disturbance. For the purpose of obtaining high dynamic performance, recently researchers developed several non-linear as well as intelligent controllers. Most of the reported works on controller design of IPMSM took an assumption of d-axis stator current (i[subscript d]) equal to zero in order to simplify the development of the controller. However, with this assumption it is not possible to control the motor above the rated speed and the reluctance torque of IPMSM can not be utilized efficiently. Furthermore, this assumption leads to an erroneous result for motor at all operating conditions. In this thesis, some controllers are developed for the IPMSM drive system incorporating the flux-weakening technique in order to control the motor above the rated speed. A detailed analysis of the flux control based on various operating regions is also provided in this thesis. In order to get the optimum efficiency, an adaptive backstepping based nonlinear control scheme incorporating flux control for an IPM synchronous motor drive is taken into account at the design stage of the controller. Thus, the proposed adaptive nonlinear backstepping controller is capable of conserving the system robustness and stability against all mechanical parameters variation and external load torque disturbance. To ensure stability the controller is designed based on Lyapunov's stability theory. A novel fuzzy logic controller (FLC) including both torque and flux control is also developed in this work. The proposed FLC overcomes the unknown and nonlinear uncertainties of the drive and controls the motor over a wide speed range. For further improvement of the FLC structure, the membership function of the controller is tuned online. An integral part of this work is directed to develop an adaptive-network based fuzzy interference system (ANFIS) based neuro fuzzy logic controller. In this work, an adaptive tuning algorithm is also developed to adjust the membership function and consequent parameters. In order to verify the effectiveness of the proposed IPMSM drive, at first simulation model is developed using Matlab/Simulink. Then the complete IPMSM drive incorporating various control algorithms have been successfully implemented using digital signal processor (DSP) controller board-DSI104 for a laboratory 5 hp motor. The effectiveness of the proposed drive is verified both in simulation and experiment at different operating conditions. The results show the robustness of the drive and it's potentiality to apply for real-time industrial drive application. This thesis also provides through knowledge about development and various speed real-time applications of controllers for IPMSM drive, which will be useful for researchers and practicing engineers

Traction control in electric vehicles

Tese de Mestrado Integrado. Engenharia Electrotécnica e de Computadores. Área de Especialização de Automação. Faculdade de Engenharia. Universidade do Porto. 201

Advanced Mathematics and Computational Applications in Control Systems Engineering

Control system engineering is a multidisciplinary discipline that applies automatic control theory to design systems with desired behaviors in control environments. Automatic control theory has played a vital role in the advancement of engineering and science. It has become an essential and integral part of modern industrial and manufacturing processes. Today, the requirements for control precision have increased, and real systems have become more complex. In control engineering and all other engineering disciplines, the impact of advanced mathematical and computational methods is rapidly increasing. Advanced mathematical methods are needed because real-world control systems need to comply with several conditions related to product quality and safety constraints that have to be taken into account in the problem formulation. Conversely, the increment in mathematical complexity has an impact on the computational aspects related to numerical simulation and practical implementation of the algorithms, where a balance must also be maintained between implementation costs and the performance of the control system. This book is a comprehensive set of articles reflecting recent advances in developing and applying advanced mathematics and computational applications in control system engineering