Top PDF Control of brushless DC motor using siingle-input fuzzy proportional-integral controller

Control of brushless DC motor using siingle-input fuzzy proportional-integral controller

Control of brushless DC motor using siingle-input fuzzy proportional-integral controller

Since the 1990’s, the Proportional-Integral (PI) controller is widely known and used in electric drive field due to its fast and efficient response [5]. PI controller is a linear controller that implements a well-established design procedure such as bode-plot technique, Nyquist and etc. In addition, the performance of this type of controller is easy to analyze using several mathematical and computer tools that have been established. PI controller has a few disadvantages and the most known is its limitation of operating well in one point. Thus, as it is desirable to have variable- speed operation in a non-linear system, PI controller may not be the best option. Other than that, PI controller also has slow computation, oscillation and overshoot problems and complicated mathematical model [5, 6]. Non-model based method such as Neural Network and Fuzzy Logic can help get rid of the problem in deriving the mathematical model of a system.
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Title :    SINGLE INPUT FUZZY PID CONTROLLER (SIFPIDC) BASED SPEED CONTROL FOR BRUSHLESS DC MOTOR DRIVEAuthor (s) : K.Manojkumar, D.Sivranjani, K.Sridharan, M.Ragul, B.M.Prabhu

Title : SINGLE INPUT FUZZY PID CONTROLLER (SIFPIDC) BASED SPEED CONTROL FOR BRUSHLESS DC MOTOR DRIVEAuthor (s) : K.Manojkumar, D.Sivranjani, K.Sridharan, M.Ragul, B.M.Prabhu

Abstract—BLDC motor is a synchronous motor that commonly used in various application either industrial or domestically. In this paper Single Input Fuzzy PID Controller (SIFPIDC) were used as a speed controller for brushless DC motor (BLDC) drive. A simplified FLC has been developed by reducing the number of rules to solve the problems of lengthy design time cycle. SIFPIDC has simple generation and tuning process and provides an exceptional response for cases of large signal disturbance. The control structure of BLDC motor drive is fed up by 3 phase inverter and has 2 closed loops, where the inner loop is to control the current while the outer loop to control the speed of the motor. Simulation is done by using MATLAB/Simulink with fuzzy control and its input values are modelled using fuzzy toolbox. The Simulation result is observed through speed response, torque ripple, torque output under normal condition and fuzzy logic condition. SIFPIDC is as expected to produce a response which is similar to the conventional PID controller.
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Speed Control Of Brushless Dc Motor Using Neuro Fuzzy Based Pid Controller

Speed Control Of Brushless Dc Motor Using Neuro Fuzzy Based Pid Controller

_____________________________________________________________________________________________________ Abstract—The main purpose of this proposed research paper is to control of brushless DC motor using Neuro fuzzy based PID controller . This research discribes modeling of four switch inverter fed BLDC motor explained with transfer function model. The control with sensor , the controller is used Neuro fuzzy based PID controller & in sensorless control the method is terminal sensing . Simulation of BLDC with NFPID controller .Speed control method of BLDC motor with NFPID controller.Comparative analysis of sensor & sensorless control of four switch inverter fed to BLDC motor.
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Speed Control of Brushless DC Motor based on Fractional Order PID Controller

Speed Control of Brushless DC Motor based on Fractional Order PID Controller

The drive system consists of a BLDC motor, three phase inverter, DC-DC converter and controller. The speed of BLDC motor is directly proportional to its terminals voltages. The terminals voltages are changed using DC- DC converter connected at the input of the inverter. The proposed control system consists of proposed rotor position scheme, which detect the rotor speed, to provide proper commutation sequence to the inverter and FOPID controller to control the duty cycle of the DC-DC converter using PWM technique . The schematic block diagram for the drive system of brushless dc motor is shown in Fig.5. The simulink model is shown in Fig.6. The brushless DC motor can be built according to the mathematical modeling in equations [1-10].
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Rotational Speed Control of Brushless Dc Motor  Using Genetic Algorithm Optimized PD Controller

Rotational Speed Control of Brushless Dc Motor Using Genetic Algorithm Optimized PD Controller

Brushless DC motor (BLDC) has been widely used for many years in many industrial application because of its efficiency and reliability. There has been a massive research interest in the area of modelling and control of BLDC as reported in the literatures. Recent research, for instance, an efficient ANFIS based speed controller for BLDC motor is proposed as in [1]. ANFIS controller is modelled through modified data of the fuzzy tuned PID controller and is simulated under varying speed and load conditions. Control system responses shows that the proposed controller is superior to the classical PI and fuzzy tuned PID controller and fuzzy variable structure controller. Bat algorithm optimized online ANFIS for the same plant is also proposed [2]. Their results show that the proposed controller eliminates the uncertainty problem due to load disturbance and enhance the time domain specifications and performances in all operating conditions. The same algorithm is then enhanced using the same system by proposing a fuzzy online gain tuned windup PID and fuzzy PID supervised ANFIS [3]. The results show that the windup problem can be eliminated and also improve control system performances.
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Brushless DC motor tracking control using self-tuning fuzzy PID control and model reference adaptive control

Brushless DC motor tracking control using self-tuning fuzzy PID control and model reference adaptive control

Abstract This paper compares the performance of two different control techniques applied to high performance brushless DC motor. The first scheme is self-tuning fuzzy PID controller and the sec- ond scheme is model reference adaptive control (MRAC) with PID compensator. The purpose of the control algorithm was to force the rotor speed to follow the desired reference speed with good accuracy all time. This objective should be achieved for different speed/time tracks regardless of load disturbance and parameter variations. The simulation results presented show that the second control scheme has better performance.
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Speed Control of Brushless DC Motor Using Proportional Integral Controller

Speed Control of Brushless DC Motor Using Proportional Integral Controller

Abstract: Ease control and high power density are the two main reasons for using brushless DC motor in wide range of industrial applications. In general the brushless DC motors are controlled using power Semiconductor bridge. So the rotor position sensors are used in the inverter bridge for starting and to provide proper commutation sequence to the power switches. In building inverter bridge power switches are used due to high reliability and performance. In this paper the three phase brushless DC motor model is designed with proportional integral controller and tested in MATLAB software. The PI controller is used to control the speed of the brushless DC motor. On the other hand parameters like Back EMF, current, speed and torque are evaluated for the designed models of BLDC motor. Due to the easy implementation and simple control structure the convectional PI controller are used in industries.
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Modeling and Control of DC Chopper Fed Brushless DC Motor

Modeling and Control of DC Chopper Fed Brushless DC Motor

industrial and household applications due to its higher efficiency, reliability and better performance compared to Brushed motor. In this paper, various methods of speed control for Brushless DC motor has been included. The dynamic model of the BLDC motor is developed and further analysis has been conducted for the selection of controllers. A comparative study between the Performance of BLDC motor fed with P, PI and PID controllers are included. The implementation includes both direction and open loop speed control. Simulation is carried out using MATLAB / SIMULINK for 120 degree mode of operation. The results show that the performance of BLDC Motor is quite satisfactory for various transient conditions with PID controllers.
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Speed Control of Brushless DC Motor Using Model Reference Adaptive Control

Speed Control of Brushless DC Motor Using Model Reference Adaptive Control

ABSTRACT: Brushless DC motor drives are widely used in various industrial systems, such as servomotor drives, medical, automobile and aerospace industry. These are electronically commutated motor and offer many advantages over brushed DC motors which include increased efficiency, longer life, low volume and high torque. The main objective of the thesis is to design a controller to keep the output speed of the BLDC motor constant, under different operating conditions such as parameter variations, load disturbances etc. In model reference adaptive control, the plant output is varied with respect to the output of the reference model with some adjusting mechanism in order to obtain the speed control. The platform for modelling of BLDC motor and simulation of the control is MATLAB/Simulink
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Speed and torque control of resonant inverter fed brushless dc motor drive using fuzzy logic controller

Speed and torque control of resonant inverter fed brushless dc motor drive using fuzzy logic controller

Abstract— This paper presents a comparative analysis of speed control of brushless DC motor (BLDC) drive fed with conventional two-level, three and five level diode clamped resonant inverter (DC- MLI). The performance of the drive system is successfully evaluated using Fuzzy Logic (FL) based speed controller. The control structure of the proposed drive system is described. The speed and torque characteristic of conventional two-level inverter is compared with the three and five-level resonant inverter (MLI) for various operating conditions. The three and five level diode clamped resonant inverters are simulated using IGBT’s and the mathematical model of BLDC motor has been developed in MATLAB/SIMULINK environment. The simulation results show that the Fuzzy based speed controller eliminate torque ripples and provides fast speed response. The developed Fuzzy Logic model has the ability to learn instantaneously and adapt its own controller parameters based on disturbances with minimum steady state error, overshoot and rise time of the output voltage.
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Speed Control of Brushless DC Motor Using Fuzzy Based Controllers

Speed Control of Brushless DC Motor Using Fuzzy Based Controllers

providing proper commutation sequence to turn on the power devices in the inverter bridge. Based on the rotor position, the power devices are commutated sequentially every 60 degrees. The electronic commutation eliminates the problems associated with the brush and the commutator arrangement, namely sparking and wearing out of the commutator brush arrangement, thereby, making a BLDC motor more rugged compared to a dc motor. The brush less dc motor consist of four main parts Power converter, permanent magnet brushless DC Motor (BLDCM), sensors and control algorithm. The power converter transforms power from the source to the BLDCM which in turn converts electrical energy to mechanical energy. The circuit configuration of three phase inverter fed BLDC motor is shown in Fig.1.
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Brushless DC Motor Speed Control using PID Controller, Fuzzy Controller, and Neuro Fuzzy Controller

Brushless DC Motor Speed Control using PID Controller, Fuzzy Controller, and Neuro Fuzzy Controller

Brushless dc motors (BLDC motors) are commonly used nowadays in industry and at many applications according to its very high speed with a very compact size in comparison to the older motors with brushes, moreover the importance of being powered by direct current (DC) and without all disadvantages of using brushes, which is convenient to many applications like hard drivers, CD/DVD players, electric bicycles, electric and hybrid vehicles, CNC machines and Aero modeling. The purpose of this paper is to control the speed of a brushless dc motor by using PID controller, Fuzzy logic controller, and Neuro fuzzy controller. According to these varieties of control techniques which used to control the speed, we have many parameters which used to assess that which controller will be better to use.
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A Comparative Study of PID and Fuzzy Controller for Speed Control of Brushless DC Motor Drive

A Comparative Study of PID and Fuzzy Controller for Speed Control of Brushless DC Motor Drive

applications such as in battery operated vehicles, wheel chairs, automotive fuel pumps, machine tools, robotics, aerospace and in other various industrial applications because of their superior electrical and mechanical characteristics. The conventional controllers fail to give the desired performance in the BLDC motor control systems due to non-linearity arising out of the variations in the system parameters and the change in load. This paper presents a comparative study between PID and Fuzzy controller for the speed control of the Brushless DC motor. MATLAB/SIMULINK is used to carry out the simulation.
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SPEED CONTROL OF BRUSHLESS DC MOTOR ON RESONANT POLE INVERTER USING FUZZY LOGIC CONTROLLER

SPEED CONTROL OF BRUSHLESS DC MOTOR ON RESONANT POLE INVERTER USING FUZZY LOGIC CONTROLLER

In this paper, a new fuzzy logic based resonant pole inverter is designed for BLDC motor drive systems which is easy to implement in industries. PI controller has also been implemented for comparison with the proposed fuzzy based control scheme With the development of power electronics technique and Permanent magnet material, permanent magnet brushless DC motor (BLDC) with trapezoidal back electromotive force(BEMF) have been widely used in many applications of variable-speed drives, which have the advantages of higher power/weight and higher efficiency. In the traditional control scheme, the armature winding on the stator of BLDC is commutated electronically by a six-step inverter that switches according to the signals of rotor position. These signals usually can be obtained from Hall Effect sensors. Moreover, the Hall Effect sensors obtain a lower resolution for the rotor angle which can cause torque ripple and degenerate its performance. In order to improve the control performance of BLDC drive
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Brushless DC Motor Speed Control using both PI Controller and Fuzzy PI Controller

Brushless DC Motor Speed Control using both PI Controller and Fuzzy PI Controller

Speed control is the process of changing the electric power delivered to the motor to achieve a certain speed which is needed. Another purpose of speed control is to keep the motor speed constant with outsource disturbances in torque. There are two main methods for controlling the speed, the Proportional integral derivative controller, and the fuzzy PI controller. In [3, 8] both conventional PI, and fuzzy PI controllers are discussed.

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Digital Signal Controller Based Digital Control of Brushless DC Motor

Digital Signal Controller Based Digital Control of Brushless DC Motor

The TMS320F2812 is a new generation controller with main frequency of 150MHz.The speed and features of this DSP make it an excellent choice for the digital control of motors. The TMS320F2812 belongs to C2000 series of DSPs of the Texas Instruments which mainly focuses on industrial purposes. It has a powerful data processing capability and high speeds. The C2000 series DSP integrates the best features of DSP and microcontroller, and the F2812 is one of the most cost - effective DSP chip. It has an efficient math ability in addition to which, it also has a relatively perfect event management capabilities and embedded control functions, therefore it is widely used in industrial control, especially in high-volume data processing measurement and control applications with high demanding of processing speed and accuracy such as in aerospace.
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An anti-windup self-tuning fuzzy PID controller for speed control of brushless DC motor

An anti-windup self-tuning fuzzy PID controller for speed control of brushless DC motor

Generally, the speed closed-loop is used to control the BLDC motors and the speed controller based on proportional-integral-derivative (PID) is widely adopted in practical application. PID control is one of the most popular control strategies and has been com- monly used in industrial control systems because of its simplicity, clear functionality, robustness and effective- ness [7,8]. However, BLDC motor is a multivariable nonlinear system, the conventional PID controller using in this system always exist some de fi ciencies. It is so sensitivity to the system uncertainties that the control performance can be seriously degraded under parameter variations. Moreover, the conventional PID controller is also difficult to tune the control parameters to adjust the high precision and rapid speed of system dynamic performance and static
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Simulation of speed control brushless dc motor using gaussian fuzzy logic controller

Simulation of speed control brushless dc motor using gaussian fuzzy logic controller

Hall sensors work on the hall-effect principle that when a current-carrying conductor is exposed to the magnetic field, charge carriers experience a force based on the voltage developed across the two sides of the conductor. If the direction of the magnetic field is reversed, the voltage developed will reverse as well. For Hall-effect sensors used in BLDC motors, whenever rotor magnetic poles North (N) or South (S) pass near the hall sensor, they generate a HIGH or LOW level signal, which can be used to determine the position of the shaft. Most BLDC motor consists of three Hall

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The Improved Performance of the Brushless DC Motor driven by using ANFIS Controller

The Improved Performance of the Brushless DC Motor driven by using ANFIS Controller

ABSTRACT:This paper presents design and simulation of a fuzzy controller for achieving better performance of Brushless DC (BLDC) servomotor drive. The performance of fuzzy and PID controller-based BLDC servomotor drives is verified under different operating conditions such as change in reference speed , parameter variations, load disturbance, etc. BLDC servomotors are used in aerospace, instrumentation systems, space vehicles, electric vehicles, robotics, and industrial control applications. In such applications, conventional controllers like P, PI, and PID are being implemented with the BLDC servomotor drive control systems to achieve satisfactory transient and steady-state responses. However, the major problem occuring with the conventional PID controller is that the tuned gain parameters obtained from the BLDC servomotor drive control systems can not yield better transient andSteady-state responses under different operating conditions such as parameter variations, load disturbances, etc. The execution is contrasted with PID controller in order to demonstrate its ability to track the error and value of fuzzy controller in control applications .
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Design of Brushless DC Motor with Fuzzy Logic Controller

Design of Brushless DC Motor with Fuzzy Logic Controller

Abstract - Actually brushless DC motor is the alternate motor for traditional motors and also comparatively brushless DC motor has improved performance in speed, torque, efficiency and electromagnetic torque. In this paper the three phase brushless DC motor model is designed with fuzzy logic controller and tested in MATLAB software. The Fuzzy logic controller is used to control the speed of the brushless DC motor. On the other hand parameters like Back EMF, current, speed and torque are evaluated for the designed models of BLDC motor.
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