scholarly journals Performance Study of Enhanced Non-Linear PID Control Applied on Brushless DC Motor

2018 ◽  
Vol 9 (2) ◽  
pp. 536 ◽  
Author(s):  
Mohamed Shamseldin ◽  
Mohamed Abdel Ghany ◽  
Abdel Ghany Mohamed
Keyword(s):  
Pid Control ◽  
Dc Motor ◽  
Control Technique ◽  
Brushless Dc Motor ◽  
Performance Study ◽  
Brushless Dc ◽  
Speed Regulation ◽  
Speed Tracking ◽  
Motor Drive System ◽  
Fractional Order Pid

<span style="color: black; font-family: 'Times New Roman',serif; font-size: 9pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA; mso-bidi-font-style: italic;">This paper presents an enhanced nonlinear PID (NPID) controller to follow a preselected speed profile of brushless DC motor drive system. This objective should be achieved regardless the parameter variations, and external disturbances. The performance of enhanced NPID controller will be investigated by comparing it with linear PID control and fractional order PID (FOPID) control. These controllers are tested for both speed regulation and speed tracking. The optimal parameters values of each control technique were obtained using Genetic Algorithm (GA) based on a certain cost function. Results shows that the proposed NPID controller has better performance among other techniques (PID and FOPID controller).</span>

scholarly journals PID Control System on Brushless DC Motor for Quadcopter Balance

Jurnal INFORM ◽  
2021 ◽  
Vol 6 (2) ◽  
pp. 110-114
Author(s):  
Mochamad Mobed Bachtiar ◽  
Fernando Ardilla ◽  
Muhammad Faiz Hasbi ◽  
Iwan Kurnianto Wibowo
Keyword(s):  
Pid Control ◽  
Control Method ◽  
Dc Motor ◽  
Unmanned Aircraft ◽  
Integrated System ◽  
Brushless Dc Motor ◽  
Test Results ◽  
Brushless Dc ◽  
Aerial Vehicle ◽  
Aircraft System

Unmanned Aerial Vehicle (UAV) is an unmanned aircraft system that is no longer a special need but has become a general need for the community, and one example is used to capture everyday moments through photos or videos from the air. Among the models of UAV aircraft is the quadcopter, where there is a flight controller that functions to fly the quadcopter by adjusting the speed of each motor. The flight controller that is often used today is the Pixhawk manufacturer. The Pixhawk module is an integrated system that the factory has provided, so it cannot be modified in terms of control and I/O. This research focuses on making an independent flight controller that can be used to fly a quadcopter. The control method that is implanted is Proportional Integral Derivative or commonly known as PID. The flight controller uses the PID control method to adjust each Brushless DC Motor (BLDC) speed to maintain stability while flying. From the test results, the quadcopter can fly stably with KP parameters of 2.5, KI of 0.6, and KD of 1.0. The response time in processing feedback is 3s.

Analysis and Experimental Validation of Performance of Z-Source Inverter-Fed Permanent Magnet Brushless DC Motor Drive

2011 ◽  
Vol 383-390 ◽  
pp. 7063-7068 ◽  
Author(s):  
Jian Shang ◽  
Zhi Zhen Liu ◽  
Yan Zhang
Keyword(s):  
Permanent Magnet ◽  
Current Source ◽  
Dc Motor ◽  
Drive System ◽  
Voltage Source ◽  
Brushless Dc Motor ◽  
Motor Drive ◽  
Brushless Dc ◽  
Permanent Magnet Brushless Dc ◽  
Motor Drive System

The Z-source inverter has overcome the limitation of the conventional voltage source inverter and current source inverter and provides a new option for motor drive system. The Z-source inverter has the unique ability of boosting the voltage of the dc source, which has advantages in the motor drive system for electric vehicles where the voltage of the onboard battery is usually lower. Firstly, this paper analyses the speed characteristic of permanent magnet brushless dc motor. Then operation principles and the control method are described and an effective and convenient strategy for generating PWM pluses with shoot-through states based on TMS320F2812 DSP is introduced. At last, the results of this experiment are presented and verify the correctness of the model.

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