Hardware-Software Co-Design for BLDC Motor Speed Controller Design

2012 ◽  
Vol 463-464 ◽  
pp. 1256-1259 ◽  
Author(s):  
Bogdan Alecsa ◽  
Alexandru Onea
Keyword(s):  
Control Algorithm ◽  
Controller Design ◽  
Liquid Crystal Display ◽  
Data Communication ◽  
Bldc Motor ◽  
Motor Speed ◽  
Brushless Dc ◽  
Speed Controller ◽  
Serial Data ◽  
Field Programmable

This paper proposes a combined hardware-software approach for a controller design. The case of a brushless DC (BLDC) motor speed controller is studied. A hardware controller is implemented inside a field programmable gate array (FPGA) device, together with soft core processors that implement by software non-critical tasks, like liquid crystal display (LCD) interface and serial data communication to a host computer. This way, the control algorithm is executed in hardware, as fast as possible, while the monitoring tasks are performed by the software. Experimental results are provided, showing the working design.

scholarly journals Brushless DC Motor Speed Controller for Electric Motorbike

2018 ◽  
Vol 9 (2) ◽  
pp. 859
Author(s):  
Mohd Syakir Adli ◽  
Noor Hazrin Hany Mohamad Hanif ◽  
Siti Fauziah Toha Tohara
Keyword(s):  
Pid Controller ◽  
Dc Motor ◽  
Battery Pack ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Motor Speed ◽  
Brushless Dc ◽  
Speed Controller ◽  
Optimum Speed ◽  
Control Scheme

<p>This paper presents a control scheme for speed control system in brushless dc (BLDC) motor to be utilized for electric motorbike. While conventional motorbikes require engine and fuel, electric motorbikes require DC motor and battery pack in order to be powered up. The limitation with battery pack is that it will need to be recharged after a certain period and distance. As the recharging process is time consuming, a PID controller is designed to maintain the speed of the motor at its optimum state, thus ensuring a longer lasting battery time (until the next charge). The controller is designed to track variations of speed references and stabilizes the output speed accordingly. The simulation results conducted in MATLAB/SIMULINK® shows that the motor, equipped with the PID controller was able to track the reference speed in 7.8x10<sup>-2</sup> milliseconds with no overshoot.  The result shows optimistic possibility that the proposed controller can be used to maintain the speed of the motor at its optimum speed.</p>

scholarly journals Comparison between Fuzzy Logic and PI Control for The Speed Of BLDC Motor

2018 ◽  
Vol 9 (3) ◽  
pp. 1116 ◽  
Author(s):  
Akram H. Ahmed ◽  
Abd El Samie B. Kotb ◽  
Ayman M. Ali
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Bldc Motor ◽  
Motor Speed ◽  
Proportional Integral ◽  
Brushless Dc ◽  
Speed Controller ◽  
Torque Response ◽  
High Degree

In this paper the analytical comparison of brushless DC (BLDC) motor drive with proportional integral (PI) and fuzzy logic controller (FLC) based speed controllers is estimated. Proportional integral (PI) has disadvantages like it do not operate properly when the system has a high degree of load disturbances.<em> </em>In recent years, the application of fuzzy logic controller (FLC) for high dynamic performance of motor drives has become an important tool. FLC is a good for load disturbances and can be easily implemented. The modeling and simulation of both the speed controllers have been made by MATLAB/SIMULINK. The dynamic characteristics of the BLDC motor (speed and torque) response, obtained under PI and Fuzzy logic based speed controller, are compared for various operating condition.

scholarly journals Soft Computing Technique of Bridgeless SEPIC Converter for PMBLDC Motor Drive

2018 ◽  
Vol 9 (4) ◽  
pp. 1503
Author(s):  
Meena Devi R. ◽  
L. Premalatha
Keyword(s):  
Control Method ◽  
Motor Drive ◽  
Bldc Motor ◽  
Motor Speed ◽  
Computing Technique ◽  
Brushless Dc ◽  
Speed Controller ◽  
Three Phase ◽  
Soft Computing Technique ◽  
Conduction Mode

A novel speed controller for the three-phase Brushless DC (BLDC) Motor Drive is proposed using a closed-loop AC-DC Bridgeless SEPIC Converter in continuous Conduction mode. This design proposes a single stage AC-DC converter with ON and OFF state equivalent circuits for 400W, 48V at 2450 rpm PMBLDC motor drive. The Fuzzy based voltage and current controlling method is proposed in this design. The voltage controlling method is used to control the speed for BLDC motor and the current controlling method is used to improve the power factor in AC supply. The speed of BLDC motor is observed with voltage disturbance and the constant motor speed is maintained. The proposed control method on SEPIC converter fed PMBLDC motor drive is modeled by Simulink/Matlab.

scholarly journals Optimal PID controller of a brushless dc motor using genetic algorithm

2019 ◽  
Vol 10 (2) ◽  
pp. 822 ◽  
Author(s):  
Muhammed A. Ibrahim ◽  
Ausama Kh. Mahmood ◽  
Nashwan Saleh Sultan
Keyword(s):  
Genetic Algorithm ◽  
System Performance ◽  
Pid Controller ◽  
Controller Design ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Motor Speed ◽  
Error Criterion ◽  
Brushless Dc

Brushless DC (BLDC) motor is commonly employed for many industrial applications due to their high torque and efficiency. This article produces an optimal designed controller of Brushless DC motor speed control depending on the genetic algorithm (GA). The optimization method is used for searching of the ideal Proportional–Integral-Derivative (PID) factors. The controller design methods of brushless DC motor includes three kinds: trial and error PID design, auto-tuning PID design and genetic algorithm based controller design. A PID controller is utilizing by conducted Integral absolute error criterion (IAE) and integral squared error (ISE) error criterion for BLDC motor control system. A GA-PID controller is designed to enhance the system performance by means of genetic algorithm. PID controller coefficients are calculated by GA to produce optimal PID as  hybrid PID with GA controller .The closed loop speed response of PID controller is experimented  for IAE and ISE error criteria. The suggested controller GA_PID is planned, modeled and simulated by MATLAB/ software program. A comparison output system performance monitored for every controller schemes. The results display that the time characteristics performance of GA-PID controller based on ISE objective function has the optimal performance (rise time, settling time, percentage overshoot) with other techniques.

ANFIS — Fractional order PID with inspired oppositional optimization based speed controller for brushless DC motor

2019 ◽  
Vol 18 (01) ◽  
pp. 1941004 ◽  
Author(s):  
K. Balamurugan ◽  
R. Mahalakshmi
Keyword(s):  
Fractional Order ◽  
Fuzzy Inference ◽  
Bldc Motor ◽  
Inference System ◽  
Tuning Parameters ◽  
Brushless Dc ◽  
Speed Controller ◽  
Speed Tracking ◽  
Neuro Fuzzy ◽  
Fractional Order Pid

Due to the expanded industrialization, the necessity of variable speed machines/drives keeps on expanding. The vast majority of computerized Brushless Direct Current (BLDC) motor frame-works are utilized because of their speedier reaction and high stablity. In this paper, an innovative technique, i.e. Adaptive Neuro-Fuzzy Inference System (ANFIS) with Fractional-Order PID (FOPID) controllers for controlling a portion of the parameters, for example, speed, and torque of the BLDC motor are exhibited. With a specific end goal being the performance of the proposed controller under outrageous working conditions, for example, varying load and set speed conditions, simulation results are taken for deliberation. An Opposition-based Elephant Herding Optimization (OEHO) optimization algorithm is utilized to improve the tuning parameters of FOPID controller. At that point, the ANFIS is gladly proposed to adequately control the speed and torque of the motor. The simulation result exhibited that the composed FOPID controller understands a decent dynamic behavior of the BLDC, an immaculate speed tracking with less ascent and gives better execution. The performance investigation of the proposed strategy lessened the error signal contrasted with the existing strategies, for example, FOPID-based Elephant Herding Optimization (EHO), Proportional–Integral–Derivative BAT (PID-BAT), and PID-ANFIS.

Research and Realization on Sensorless Brushless DC Motor Control System

2014 ◽  
Vol 687-691 ◽  
pp. 183-186 ◽  
Author(s):  
Yu Hong Liang ◽  
Hai Bo Huang ◽  
Deng Liang Cheng ◽  
Jian Ping Lan
Keyword(s):  
Motor Control ◽  
Control System ◽  
Control Algorithm ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Zero Crossing ◽  
Brushless Dc ◽  
Dc Motor Control ◽  
Motor Control System

Brushless DC Motor is a kind of a new motor which commutation signals replaces traditional motor mechanical structure with electronic signals. Square wave brushless DC motor can be divided into sensor motor and sensorless motor. Position sensor will increase system cost, motor size and maintenance difficulty, which bring about limitation and limits to promote its application in all areas. This project designs sensorless BLDC Motor control system with the core of the stm32 micro-controller and uses Back-EMF zero-crossing detection method. In the system designing software control algorithm, drawing schematic diagram of hardware and making PCB board have been completed dependently. The experimental results show that the system can well realize the starting and running of sensorless BLDC Motor control system, and have a good measure of protection.

scholarly journals BLDC Motor Speed Control using Fuzzy Logic PID Controller and Comparing It with PI Controller

2019 ◽  
Vol 9 (2) ◽  
pp. 4917-4922
Keyword(s):  
Mathematical Model ◽  
Pid Controller ◽  
High Performance ◽  
Pi Controller ◽  
Dynamic State ◽  
Bldc Motor ◽  
Fuzzy Pid ◽  
Motor Speed ◽  
Brushless Dc ◽  
Fuzzy Pid Controller

In this project, mathematical model of the Brushless DC motor (BLDC) is developed and the closed-loop Fuzzy PID controller has been simulated in MATLAB-Simulink environment. The three-phase (BLDC) is developed and the DC power is supplied to this machine though six step inverter whose switching state is controlled by the hall signal. The hall effect sensor senses the rotor posit ion of the motor and it generates binary digit number which is decoded and given to the six-step inverter. The mathematical model is developed using the back emf equations and torque equation of the BLDC motor. The PI controller doesn’t operate properly during dynamic state and hence the fuzzy-PID-controller is better option to control and regulate the speed of the BLDC motor which has high performance in comparison to the PI controller. And, we can get the smooth speed-torque characteristics using Fuzzy PID controller.

Sign in / Sign up

Export Citation Format

Share Document