Speed Sensorless Control of Six-Phase Asynchronous Motor Drive

Multi -phase ac motor drives are nowadays considered for various applications, due to many advantages that they offer when compared to three-phase motors. Cancellation of mechanical position or speed sensors at the motor shaft have the attractions for adjustable speed drives of induction motor to reduce the cost and increase the reliability. To replace the sensor, information of the rotor speed is extracted from measured stator currents and voltages at motor terminals. This paper investigates speed estimation method using model reference adaptive system (MRAS) to improve the performance of a sensorless vector controller of six-phase induction motor (IM). In the proposed method, the stator current is used as the state variable to estimate the speed. Since the stator current error is represented as a function of the first degree for the error value in the speed estimation, the proposed method provides fast speed estimation and is also, more robust to variations in the stator resistance, compared with other MRAS methods. Consequently, this method can improve the performance of a sensorless vector controller in a low speed region and at zero-speed. The proposed method is verified by simulation using the Matlab/Simulink package. The performance of the proposed system is investigated at different operating conditions. The proposed controller is robust and suitable for high performance six-phase induction motor drives. Simulation results validate the proposed approaches

SENSORLESS SPEED ROTOR FLUX ORIENTED CONTROL OF THREE PHASE INDUCTION MOTOR

Sensorless speed rotor flux oriented control of induction motor drives it is known to produce high performance because of decoupling rotor flux and torque producing current components of stator currents. This paper describes a simple and robust sensorles speed rotor flux oriented control system for three phase induction motor drives that it is adequate for high dynamic applications. To control the rotor speed of the induction motor drives, a PI controller is included in the speed control system. A hysteresis current controllers are applied for changing the magnitude and the frequency of the output voltage of the PWM voltage source inverter which fed the induction motor. In order to verify the proposed sensorlees speed control system, the model of the system is implemented in MATLAB Simulink software, which is suitable for testing the dynamic simulation. Simulation results shows that the reference and rotor speed of induction motor are very closed to each-other under step load torque changes

A Sliding Mode Controller for Induction Motor Drives

Induction motors are being applied today to a wider range of applications requiring variable speed. Generally, variable speed drives for Induction Motor require both wide operating range of speed and fast torque response, regardless of any disturbances and uncertainties (like load variation, parameters variation and un-modeled dynamics). This leads to more advanced control methods to meet the real demand. The recent advances in the area of field-oriented control along with the rapid development and cost reduction of power electronics devices and microprocessors have made variable speed induction motor drives an economical alternative for many industrial applications. These AC drives are nowadays replacing their DC counter part and are becoming a major component in today’s sophisticated industrial manufacturing and process automation. Advent of high switching frequency PWM inverters has made it possible to apply sophisticated control strategies to AC motor drives operating from variable voltage, variable frequency source. The complexity in there mathematical model and the consequent need for the sophisticated algorithms are being handled by the computational power of low cost microprocessors to digital signal processors (DSPs). In the formulation of any control problem there will typically be discrepancies between the actual plant and the mathematical model developed for controller design. This mismatch may be due to un-modeled dynamics, variation in system parameters or the approximation of complex plant behavior by a straightforward model. The designer must ensure that the resulting controller has the ability to produce required performance levels in practice despite such plant/model mismatches. This has led to an intense interest in the development of robust control methods which seek to solve this problem. One particular approach to robust-control controller design is the so-called sliding mode control methodology. In this dissertation report, a sliding mode controller is designed for an induction motor drive. The gain and band width of the controller is designed considering rotor resistance variation, model in accuracies and load disturbance, to have an ideal speed tracking. The chattering effect is also taken into account. The controller is simulated under various conditions and a comparative study of the results with that of PI controller has been presented

Intelligent control of induction motors

This thesis presents the development and implementation of an integral field oriented intelligent control for an induction motor (IM) drive using Fuzzy Logic Controller (FLC), and an Artificial Neural Network (ANN), employing a finite element controller and making use of a Proportional Integral (PI) adaptive controller as well. An analytical model of an induction motor drive has been developed. In order to prove the superiority of the proposed controller, the performance of this controller is compared with conventional PI-based IM drives. The performance of the proposed IM drive is investigated extensively at different operating conditions in simulation. The proposed adaptive PI-based speed controller’s performance is found to be robust and it is a potential candidate for high performance industrial drive applications. The novel work focuses on using a Finite Element Controller map (FECM) to manipulate adaptive controllers for motor control drives. A digital signal processing (DSP) board DS1104 and laboratory induction motor were used to implement the complete vector control scheme. The test results have been compared with simulated results at different dynamic operating conditions. The effectiveness of this control scheme has been evaluated, and it has been found to be more efficient than the conventional PI controller

Self-Tuning Fuzzy Logic Speed Control Of Induction Motor Drives

Induction motor drives are commonly applicable in various industrial applications, such as traction system, electric vehicle and home appliances. This high performance drive require robust controller to obtain satisfactory performance in terms of speed demand change, load disturbance, inertia variation and non-linearity. Fuzzy Logic Control (FLC) is suitable for controller design especially when the system is difficult to be modelled mathematically due to its complexity, nonlinearity and imprecision. However, FLC with fixed parameters may experience degradation when the system operates away from the design point, and encounters parameter variation or load disturbance. The purpose of this project is to design and implement Self-Tuning Fuzzy Logic Controller (ST-FLC) for Induction Motor (IM)drives. The proposed self-tuning mechanism is able to adjust the output scaling factor of the output controller for main FLC. This process enhances the accuracy of the crisp output. This research begins by designing Indirect Field Oriented Control (IFOC) method fed by Hysteresis Current Controller (HCC) induction motor drive system. The FLC with fixed parameters for the speed controller comprises 9-rules are tuned to achieve best performance. Then, a simple self-tuning mechanism is applied to the main fuzzy logic speed controller. All simulations are executed by using Simulink and fuzzy tools in MATLAB software. The effectiveness of the proposed controller is determined by conducting a comparative analysis between FLC with fixed parameters and ST-FLC over a wide range of operating conditions, either in forward and reverse operations, load disturbance or inertia variations. Finally, experimental investigation is carried out to validate the simulation results by the aid of digital signal controller board dSPACE DS1104 with the induction motor drives system. Based on the results, ST-FLC has shown superior performance in transient and steady state conditions in term of various performance measures such as overshoot, rise time, settling time and recovery time over wide speed range operation. In comparison to fixed parameter FLC, the proposed ST-FLC reduced the settling time by 40.5%, rise time by 47.3% and speed drop by 19.2%. The proposed self-tuning mechanism is relatively simpler and consumes less computational burden compared to other self-tuning methods. This is proved by measuring the computational burden of another Self-Tuning method which used fuzzy rules to tune the output scaling factor. The execution time of the proposed self-tuning found to be 0.5 x10−3 seconds compared to 1.2 x10−3 seconds for the other self-tuning

A Novel Self-Tuning Fuzzy Logic Controller Based Induction Motor Drive System: An Experimental Approach

High-performance induction motor (IM) drives require fast dynamic responses, robust to parameter variations, withstand load disturbance, stable control systems, and support easy hardware/software implementation. Fuzzy logic control (FLC) for speed controllers is garnering attention from researchers, since it is proven to produce better results compared with the conventional PI speed controllers. However, fixed parameter FLC experiences performance degradation when the system operates away from the design point or is affected by parameter variations or load disturbances. The purpose of this paper is to design and implement a simple self-tuning fuzzy logic controller (ST-FLC) for IM drives application. The proposed self-tuning mechanism is able to adjust the output scaling factor of the main FLC speed controller by improving the accuracy of the crisp output. The IM drive employed an indirect field-oriented control (IFOC) method fed by a hysteresis current controller (HCC). The fixed parameter FLC for the main speed controller comprises nine rules that are tuned to achieve the best performance. Then, a simple self-tuning mechanism is applied to the main fuzzy logic speed controller. All simulation work was done using Simulink and fuzzy tools in the MATLAB software. The effectiveness of the proposed controller was investigated by conducting a comparative analysis between fixed parameter FLC and ST-FLC in forward and reverse speed operations, with and without load disturbances. Finally, the experimental testing was carried out to validate the simulation results with the aid of a digital signal controller board, dSPACE DS1104, with an induction motor drive system. Based on the results, the ST-FLC showed superior performance in transient and steady-state conditions in terms of various performance measures, such as overshoot, rise time, settling time, and recovery time

To develop an efficient variable speed compressor motor system

This research presents a proposed new method of improving the energy efficiency of a Variable Speed Drive (VSD) for induction motors. The principles of VSD are reviewed with emphasis on the efficiency and power losses associated with the operation of the variable speed compressor motor drive, particularly at low speed operation.The efficiency of induction motor when operated at rated speed and load torque is high. However at low load operation, application of the induction motor at rated flux will cause the iron losses to increase excessively, hence its efficiency will reduce dramatically. To improve this efficiency, it is essential to obtain the flux level that minimizes the total motor losses. This technique is known as an efficiency or energy optimization control method. In practice, typical of the compressor load does not require high dynamic response, therefore improvement of the efficiency optimization control that is proposed in this research is based on scalar control model.In this research, development of a new neural network controller for efficiency optimization control is proposed. The controller is designed to generate both voltage and frequency reference signals imultaneously. To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. The simulation of the proposed controller for variable speed compressor is presented. The results obtained clearly show that the efficiency at low speed is significant increased. Besides that the speed of the motor can be maintained. Furthermore, the controller is also robust to the motor parameters variation. The simulation results are also verified by experiment

Observer-based Fault Detection and Diagnosis for Mechanical Transmission Systems with Sensorless Variable Speed Drives

Observer based approaches are commonly embedded in sensorless variable speed drives for the purpose of speed control. It estimates system variables to produce errors or residual signals in conjunction with corresponding measurements. The residual signals then are relied to tune control parameters to maintain operational performance even if there are considerable disturbances such as noises and component faults. Obviously, this control strategy outcomes robust control performances. However, it may produce adverse consequences to the system when faults progress to high severity. To prevent the occurrences of such consequences, this research proposes the utilisation of residual signals as detection features to raise alerts for incipient faults. Based on a gear transmission system with a sensorless variable speed drive (VSD), observers for speed, flux and torque are developed for examining their residuals under two mechanical faults: tooth breakage with different degrees of severities and shortage of lubricant at different levels are investigated. It shows that power residual signals can be based on to indicate different faults, showing that the observer based approaches are effective for monitoring VSD based mechanical systems. Moreover, it also shows that these two types fault can be separated based on the dynamic components in the voltage signals