OTA-C Realization of An Optimized FOPID Controller for BLDC Motor Speed Control

2021 ◽  
pp. 1-19
Author(s):  
Mary Ann George ◽  
Dattaguru V. Kamat ◽  
Thirunavukkarasu Indiran
Keyword(s):  

Author(s):  
Basim Alsayid ◽  
Wael A. Salah ◽  
Yazeed Alawneh

<span style="font-size: 9pt; font-family: 'Times New Roman','serif'; mso-bidi-font-style: italic; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Recent developments in the field of magnetic materials and power electronics, along with the availability of cheap powerful processors, have increased the adoption of brushless direct current (BLDC) motors for various applications, such as in home appliances as well as in automotive, aerospace, and medical industries. The wide adoption of this motor is due to its many advantages over other types of motors, such as high efficiency, high dynamic response, long operating life, relatively quiet operation, and higher speed ranges. This paper presents a simulation of digital sensor control of permanent magnet BLDC motor speed using the MATLAB/SIMULINK environment. A closed loop speed control was developed, and different tests were conducted to evaluate the validity of the control algorithms. Results confirm the satisfactory operation of the proposed control algorithms.</span>



2021 ◽  
Author(s):  
Pranav Shah ◽  
Pramod Ubare ◽  
Deepak Ingole ◽  
Dayaram Sonawane




Author(s):  
Niba Shoby ◽  
Deepika Vasanthakumar ◽  
Anupama P K

- Brushless Direct Current (BLDC) motors are highly efficient motors with high reliability and a longer life span. The advent of sensor less technology has improved the performance and reliability of BLDC motor drives. This work is to analyze a drive system for BLDC motor with Four-Switch Three-Phase Inverter (FSTPI). Back Electromotive Force (EMF) Zero Crossing Detection (ZCD) method is used to estimate the rotor position. Speed control of motor is achieved by using Fuzzy Logic Controller (FLC) based closed loop control system. The Simulation was carried out using MATLAB software and motor the performance was analyzed with FLC for motor speed regulation.



2019 ◽  
Vol 1 (1) ◽  
pp. 36
Author(s):  
Ony Asrarul Qudsi ◽  
Syechu Dwitya Nugraha

This journal presents the design and implementation of BLDC motor speed control. Speed control of the BLDC motor can be done by controlling the flux produced by the BLDC motor coil. The current reading by the sensor will be processed in the flux estimator to get the flux value in the motor. By using the PI controller, the flux value generated by the coil will be controlled so that it is equal to the setpoint value that has been determined. Flux values that have the same setpoint will be converted to PWM values which will be used as input signals on the six step inverter. The test results by providing disturbance form the additional load on the motor, shows that the motor is able to maintain its speed according to the value of the speed provided. Thus, the proposed speed regulation method can work well.



2021 ◽  
Vol 5 (1) ◽  
pp. 17-25
Author(s):  
Izza Anshory ◽  
Dwi Hadidjaja ◽  
Indah Sulistiyowati

Measurement, modeling, and optimization are three important components that must be done to get a better system on the BLDC motor speed control system. The problem that arises in the BLDC motor speed control system is the instability indicated by a high overshoot value, a slow rise time value, and a high error steady-state. The purpose of this study is to increase the stability indicator by eliminating the high value of overshoot and error steady-state and increasing the value of the rise time. The method used in this research is to measure the input and output physical parameters, to model the BLDC motor plant mathematically and the last is to perform optimization using several control methods such as Proportional Integral Derivative (PID) control, fuzzy logic intelligent control, and Particle Swarm Optimization algorithm. (PSO). Experimental and simulation results show that the PSO algorithm has a better value in increasing stability indicators when compared to the other two control methods with a rise time of 0.00121 seconds, settling time of 0.00241 seconds, and overshoot of 0%.



A sensor less BLDC (Brushless Direct Current) motor speed control is performed using PSO algorithm. The PSO algorithm manages the gain value of the PID controller. The speed of the BLDC motor is provided as the feedback to the controller. The error value is calculated by predetermined speed for the BLDC motor. Wind power generator is used as the input power source for driving BLDC motor. The output power of the wind power generator varies based on the wind speed. The variable input source for the BLDC motor affects the performance of the motor. In order to regulate the input voltage of the BLDC motor, SEPIC DC-DC converter is used. The PSO-PID controller controls the Gate pulse of the SEPIC converter. The model is developed in MATLAB/Simulink, the performance of the proposed PSO-PID control is measured in variable input power condition. The hardware model is developed using MSP430 microcontroller to test the efficiency of the PSO-PID controller in the real time environment.



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