A Fractional Order Controller for Sensorless Speed Control of an Induction Motor (original) (raw)
Energies
Agriculture activities are completely dependent upon energy production worldwide. This research presents sensorless speed control of a three-phase induction motor aided with an extended Kalman filter (EKF). Although a proportional integral (PI) controller can ensure tracking of the rotor speed, a considerable magnitude of ripples is present in the torque generated by a motor. Adding a simple derivative to have a proportional integral derivative (PID) action can cause a further increase in ripple magnitude, as it allows the addition of high-frequency noise in the system. Therefore, a fractional-order-based PID control is presented. The proposed control scheme is applied in a closed loop with the system, and simulation results are compared with the PID controller. It is evident from the results that the fractional order control not only ensures 20 times faster tracking, but ripple magnitude in torque was also reduced by a factor of 50% compared to that while using PID and ensures the ...
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Recently, speed sensorless control of Induction Motor (IM) drives received great attention to avoid the different problems associated with direct speed sensors. Among different rotor speed estimation techniques, Model Reference Adaptive System (MRAS) schemes are the most common strategies employed due to their relative simplicity and low computational effort. In this paper a novel adaptation mechanism is proposed which replaces normally used conventional Proportional-Integral (PI) controller in MRAS adaptation mechanism by a Fractional Order PI (FOPI) controller. The performance of two adaptation mechanism controllers has been verified through simulation results using MATLAB/SIMULINK software. It is seen that the performance of the induction motor has improved when FOPI controller is used in place of classical PI controller.
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FOREX Publication, 2024
Traditional induction motor control methods typically require feedback from sensors like encoders or resolvers to determine the motor's rotor position and speed accurately. The speed control of a sensorless induction motor is critical, so this study provides a novel method that combines the Model Reference Adaptive System (MRAS) for speed estimate with the Fractional Order PID controller for speed control. This controller's parameters are optimized using the Grey Wolf Optimizer Algorithm. After being implemented in the MATLAB/Simulink environment, the suggested approach's performance is compared to that of a standard PI controller. From the findings, it is clear that the proposed method effectively maintaining the specified speed as compared with PI controller. The proposed controller performance is also validated through experimental results.
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International Journal of Electrical and Computer Engineering (IJECE)
Conventional direct torque control (DTC) is one of the best control systems for regulating the torque of an induction motor (IM). However, the DTC’s enormous waves in flux and torque cause acoustic noise that degrades control performance, especially at low speeds due to the DTC’s low switching frequency. Direct torque control systems, which focus just on torque and flux, have been proposed as a solution to these problems. In order to improve DTC control performance, this work introduces a fractional-order fuzzy logic controller method. The objective is to analyze this technique critically with regard to its efficacy in reducing ripple, its tracking speed, its switching loss, its algorithm complexity, and its sensitivity to its parameters. Simulation in MATLAB/Simulink verifies the anticipated control approach’s performance.
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Speed Control of Brushless DC Motor based on Fractional Order PID Controller
Increasing the methods of order calculus for Fractional Order Proportional Integral Derivative (FOPID) controller leads to a wide applications for this type of controller in control systems. A closed loop speed control for BrushLess Direct Current (BLDC) motor with FOPID controller runs the motor very close to the reference speed, provides a good performance and robustness compared with a corresponding system using conventional PID controller. In this paper, the BLDC motor is modeled and simulated in Matlab/Simulink for speed control strategy. A DC link speed control strategy is proposed and implemented. The FOPID speed controller parameters (Kp, ki, kd, λ) are optimized by genetic evolutionary programming module. The effectiveness of the proposed speed control is verified through simulation. The control system is extra tested under a conditions of some motor parameters perturbations. The simulation results reveal a flexible and stable control strategy.
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Impact of fractional filter in PI control loop applied to induction motor speed drive
Electrical Engineering & Electromechanics
Introduction. One of the main problems of electrical machine control systems is to obtain a satisfactory performance in the rejection of load disturbances, as well as in the set-point tracking tasks. Generally, the development of control algorithms does not take into account the presence of noise. Appropriate filtering is, therefore, essential to reduce the impact of noise on the output of the controller, in addition to the machine output. Recently, there has been a great tendency toward using fractional calculus to solve engineering problems. The filtering is one of the fields in which fractional calculus has received great attention. The importance of filters in signal processing and other engineering areas is unquestionable Novelty. The proposed work is intended to be a contribution in the recent works conducted on the influence of the fractional filtering on the control robustness of induction machines control. Purpose. The main contribution of this research is the application o...
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