Top PDF Fuzzy logic control of induction motor drive for performance improvement

Fuzzy logic control of induction motor drive for performance improvement

Fuzzy logic control of induction motor drive for performance improvement

In recent years the control of high-performance induction motor drives has received widespread research interests. It has been valued more not only because it is the most used motor in industries but also due to their varied modes of operation. Also it has good self-starting capability, simple, rugged structure, low cost and reliability etc. Main property that makes it more useful for industries is its low sensibility to disturbance and maintenance free operation. Despite of many advantages of induction motor there are some disadvantages also. Like it is not true constant speed motor, slip varies from less than 1% to more than 5%. Also it is not capable of providing variable speed operation. But as it is so useful for industries we have to find some solution to solve these limitations and the solution is speed controller, that can take necessary control action to provide the required speed. Not only speed, it can control various parameters of the induction machine such as flux, torque, voltage, stator current. Out of the several methods of speed control of an induction such as changing no of pole, rotor resistance control, stator voltage control, slip power recovery scheme and constant V/f control, the closed loop constant V/f speed control method is most popular method used for controlling speed. In this method, the V/f ratio is kept constant which in turn maintains the magnetizing flux constant that eliminates harmonic problem and also the maximum torque also does not change. So, it‟s a kind of complete utilization of the motor. And the controller used are conventional P-I controller, and fuzzy logic controller.
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AC motor speed performance improvement using fuzzy logic control

AC motor speed performance improvement using fuzzy logic control

For the fuzzy logic controller, the reference speed is set as a constant. Error block generate the output which is the error between actual speed and the set speed that is applied to one input of fuzzy controller and other to store the error in the memory to compute the change in error. Multiplexer combine both inputs and give it to Fuzzy logic controller. Real time scope is used observe the actual behavioral of the system. The instrument block is used to send the output of Fuzzy Logic Controller to PIC. The Fuzzy controller in this project is design using Mamdani method as a Fuzzy Inference Scheme (FIS). The real time Fuzzy logic controller response is shown in Figure 2.6.
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Modelling and Control Strategy of Induction Motor Using Fuzzy Logic Control Technique

Modelling and Control Strategy of Induction Motor Using Fuzzy Logic Control Technique

A systematic approach of achieving robust speed control of an induction motor drive by means of Takagi-Sugeno based fuzzy control strategy has been investigated in this paper. Simulink models were developed in Matlab 7 with the TS-based fuzzy controllers (hybrid controller) for the speed control of IM. The control strategy was also developed by writing a set of 49 fuzzy rules according to the TS control strategy. The main advantage of designing the TS based fuzzy coordination scheme to control the speed of the IM is to increase the dynamic performance & provide good stabilization. Simulations were run in Matlab 7 & the results were observed on the corresponding scopes. Graphs of speed, torque, stator current, flux, etc. vs. time were observed. The outputs take less time to stabilize, which can be observed from the simulation results. But, from the incorporation of the TS based fuzzy coordination system in loop with the plant gave better results there by stabilizing the plant very quickly. The developed control strategy is not only simple, reliable, and may be easy to implement in real time applications, but also cost-effective as when this control scheme is implemented in real time, the size of the controller will become very small. Collectively, these results show that the TSfuzzy controller provides faster settling times, has very good dynamic response & good stabilization.
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THE ART OF INTELLIGENT CONTROL OF INDUCTION MOTOR DRIVE USING FUZZY LOGIC CONTROLLER

THE ART OF INTELLIGENT CONTROL OF INDUCTION MOTOR DRIVE USING FUZZY LOGIC CONTROLLER

Simulink because S-function programming knowledge is required to access the model variables. Another approach is using the Simulink Power System Block set [3] that can be purchased with Simulink. This block set also makes use of S- functions and is not as easy to work with as rest of the Simulink blocks. Reference [4] refers to an implementation approach similar to the' one in this paper but fails to give any details. In this paper, a modular, easy to understand Simulink induction motor model is described. With the modular system, each block solves one of the model equations. Though induction motors have few advantageous characteristics, they also posse's nonlinear and time- varying dynamic interactions [5 6], Using conventional PI controller, it is very difficult and complex to design a high performance induction motor drive system. The fuzzy logic control (FLC) is attractive approach, which can accommodate motor parametric variations and difficulty in obtaining an accurate mathematical model of induction motor due to rotor parametric and load time constant variations. The FLC is a knowledge-based control that uses fuzzy set theory and fuzzy logic for knowledge representation [7]. This paper presents a fuzzy logic controller suitable for speed control of induction motor drives.
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Sensorless Control of Induction Motor Drives at Low Speed Using Fuzzy Logic Control

Sensorless Control of Induction Motor Drives at Low Speed Using Fuzzy Logic Control

ABSTRACT: This paper proposes the controlling of Induction motor drives.Because of low maintenance and robustness, induction motors have many applications in industries. Speed control of induction motor is more important to achieve maximum torque and efficiency. Various control techniques such as scalar control, vector control, Sensor-less control are used. These Schemes suffers from parameter sensitivity and limited performance at low speed of operation. Sensor-less control of induction motor drive using model reference adaptive system with PI controller as reference model will limit the performance at low speed of operation. In this thesis, a novel adaptation mechanism is proposed which replaces PI controller in MRAS adaptation mechanism by a fuzzy logic controller. This is applied to a vector controlled drive and experimentally verified. This makes the reference model free from pure integration and less sensitive to stator resistance variations. This improves the performance of MRAS based sensor-less drives at low speed of operation.
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Comparative Analysis of PI Controller and Fuzzy Logic Controller for Speed Control of Three Phase Induction Motor Drive

Comparative Analysis of PI Controller and Fuzzy Logic Controller for Speed Control of Three Phase Induction Motor Drive

Today’s modern society is totally automated with less human interventions. All predictable and routines jobs are assigned to a machine. The automated machine alone does if the parameters are defined. The control algorithms and estimation of induction motor drives had grown significantly over the past few years and the innovation has furthermost propelled lately. Employing induction magnetic motor was improved enormously because of some of their advantages such as robust construction, reliable and it is free from customary maintenance. The variable speed drives for cage type induction magnetic motor requires fast torque response along with wide operating speed range irrespective of the variations in load, thus giving more advanced methods of control so as to meet the real demand. The exacting vector manages in the induction engine electric disks is all around acknowledged procedure whenever excessive degrees of effectiveness in the system reply are required. While using technique in the vector manage procedure, a induction engine has become effortlessly handled such as a on their own thrilled DC engine with regard to high performance programs and will be offering an increased a higher level active effectiveness. In addition the actual active effectiveness is actually required with regard to outstanding effectiveness associated with electric disks. These AC drives prerequisites can be satisfied by the vector control framework.
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Induction motor modelling using fuzzy logic

Induction motor modelling using fuzzy logic

In order to understand and analyze vector control, the dynamic model of the induction motor is necessary. It has been found that the dynamic model equations developed on a rotating reference frame is easier to describe the characteristics of induction motors. Any method for speed prediction is based on a model of the motor and the drive. The best accuracy of prediction for an induction motor is needed. Today, there are many choices of modelling techniques. One of them is system identification where it identifies the behaviour of a given system by estimating the model from input and output data. The estimated model is useful to simulate and predict the behaviour of the system. Not limited to that, the fitted model can be employed to regulate the output of plant.
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Induction motor controller using fuzzy logic

Induction motor controller using fuzzy logic

Volts/Hertz control is a basic control method, providing a variable frequency drive for applications like fan and pump. It provides fair speed and starting torque, at a reasonable cost. Sensor less vector control provides better speed regulation and the ability to produce a high starting torque. Flux vector control provides more precise speed and torque control with dynamic response. Field Oriented Control drives provide the best speed and torque regulation available for AC motors [6]. It provides DC like performance for AC motors, and is well suited for typical DC applications.
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Fuzzy logic based soft starting of induction motor with current control

Fuzzy logic based soft starting of induction motor with current control

Induction Motors are the most commonly used machines in industries mainly because it is robust, inexpensive and easy to maintain. For an Induction Motor, the starting current is around ten times the rated current and this persists for a few cycles. This may be very much detrimental for the machine and hence there is a need for using starters to limit the starting current. During earlier times, mechanical starters like star delta, direct online and autotransformer starters were used. Thyristorized soft starters are of low cost. Their reliability is on the higher side and they are simple and occupy lesser space, and hence their use is a fruitful solution to the induction motor starting problem. The ac motor starters incorporating power semiconductors are used frequently nowadays for their controlled soft starting ability with reduced starting current. In this study, a closed loop MATLAB SIMULINK model is developed which would reduce the current at the soft starting period. A fuzzy logic based soft start scheme for induction motor drives is used which would give optimal performance. Fuzzy logic has received higher emphasis in the field of power electronics because of its adaptive capability. The three phase stator currents are converted into two phase currents. The magnitude of current is then converted to per unit. Then it is compared with a reference value. The error is passed through a Fuzzy Logic Controller (FLC).The FLC output is used to control the amplitude of the reference sine wave. Hence by controlling the modulation index, the applied voltage to the stator is controlled and hence the starting current is limited.
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PERFORMANCE ANALYSIS OF Z-SOURCE INVERTER FED  INDUCTION MOTOR DRIVE USING FUZZY LOGIC CONTROLLER

PERFORMANCE ANALYSIS OF Z-SOURCE INVERTER FED INDUCTION MOTOR DRIVE USING FUZZY LOGIC CONTROLLER

An inverter is an electric device that converts DC to AC, the converted AC can be at any required voltage and frequency with the use of switching device and control circuits. Solid state inverters have no moving parts and are used in a wide range and application, from small switching power supplies in computers, to large electric utility high voltage dc applications that transport bulk power. Inverters are commonly used to supply AC power from DC sources such as solar panel or batteries. Inverters are used in various applications such as induction motor drives, UPS, standby power supplies, induction heating etc. Normally they are used for high power applications.
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An Optimal Fuzzy Logic Control Strategy For Switched Reluctance Motor Drive

An Optimal Fuzzy Logic Control Strategy For Switched Reluctance Motor Drive

The inherent simple construction, ruggedness, wide speed range of operation, low cost, fault tolerant capability, easy cooling simple excitation, requirement of simple converter circuit, high torque volume ratio, high efficiency and suitability under harsh environments are some of the important advantageous features of switched reluctance machine. The simple construction of the doubly salient, singly excited switched reluctance machine is shown in fig 3.1 The physical appearance of a Switched Reluctance motor is similar to that of other rotating motors (AC and DC) Induction Motor, DC motor etc. The construction of SRM is shown in figure. It has doubly salient construction. Usually the number of stator and rotor poles is even.
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Performance Analysis of Speed Control of Induction Motor using Pi, SMC & Fuzzy Logic Controller

Performance Analysis of Speed Control of Induction Motor using Pi, SMC & Fuzzy Logic Controller

Dynamic performance improved from an IM is enabled due to the development of Vector Control analysis. Just like in a dc motor, the torque and flux components can be controlled independently using vector control strategy [15]. In order to analyses vector control, we need to develop a dynamic model of the IM. This is done by converting the 3-ϕ quantities into 2-axes system called the d-axis and the q-axis. Such a conversion is called axes transformation. The d-q axes can be chosen to be stationary or rotating. Further, the rotating frame can either be the rotor oriented or magnetizing flux oriented. However, synchronous reference frame in which the d-axis is aligned with the rotor flux is found to be the most convenient from analysis point of view [8]. A major disadvantage of the per phase equivalent circuit analysis is that it is valid only if the three phase system is balanced.
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Performance Enhancement of Fuzzy Logic Duty Ratio Controller Based Direct Torque Control of Induction Motor

Performance Enhancement of Fuzzy Logic Duty Ratio Controller Based Direct Torque Control of Induction Motor

Abstract--This paper presents reduction of torque ripples in an Induction Motor with DTC by duty cycle controller. The numbers of vectors are increased beyond the available eight discrete voltage vectors are used in this paper without increasing the number of semiconductor switches in the inverter. To achieve swift response, less overshoot and precision speed control to provide to enclose torque speed characteristics, look-up table based online tuning PI controller is projected for outer speed control loop. This paper shows a new algorithm for optimized value of stator flux based on the maxim reference value of electromagnetic torque to operate in conjunction with duty ratio control. MATLAB-Simulink is used to observe the performance of proposed technique. The simulation results shows the improved results of the proposed technique compared over the existing methods.
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Torque Ripples Minimization in DTC based Induction Motor Drive using Fuzzy Logic Technique

Torque Ripples Minimization in DTC based Induction Motor Drive using Fuzzy Logic Technique

In the conventional DTC, hysteresis controllers are a two value bang bang controllers, which has the same outputs for both small and big torque errors. Therefore torque ripples are produced. The torque ripples can be minimized by dividing the torque errors into several intervals on which control action taken. In this paper fuzzy logic based direct torque control is proposed. Here two fuzzy logic controllers for both flux and torque are proposed along with space vector modulation. The fuzzy controllers allow faster response and SVM technique provide a constant inverter switching frequency so small torque ripples and current distortion.
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Performance Comparison of a Sensorless PMBLDC Motor Drive System with Conventional and Fuzzy Logic Controllers

Performance Comparison of a Sensorless PMBLDC Motor Drive System with Conventional and Fuzzy Logic Controllers

In this paper, speed control and torque ripple minimization of a sensorless Permanent Magnet Brushless DC (PMBLDC) motor drive system with varying load is analyzed. Constant speed operation with minimum torque ripple during transient state is the most difficult part in the drive system. At starting condition, if the motor is started with constant DC source, the current is too high due to the absence of back EMF. Therefore the motor will start with high torque ripples. In order to eliminate the torque ripples during starting condition by limiting the starting speed of the motor with properly designed speed controller and varying DC source from zero to its rated voltage, this will improve the reliability of PMBLDC motor. Here, the speed control and torque ripple minimization of a sensorless PMBLDC motor during starting and running condition with conventional and fuzzy logic controllers are proposed. The performance parameters of a PMBLDC motor with these controllers are analyzed through MATLAB/Simulink software.
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A Comparative Study Based on PI and Fuzzy Control of Inverter fed Induction Motor Drive

A Comparative Study Based on PI and Fuzzy Control of Inverter fed Induction Motor Drive

Induction motor drive draws heavy current during starting condition. The current is 4 to 7 times of rated current, if this current present in the motor for large time period not only it can damage insulation but conductors too. If this transient period for achieving rated speed is large it can causes above problems. The equipment which reduces the transient time of induction motor is controlled operation of Voltage Source Inverter but using this one; introduces harmonics in the machine and in system. These harmonics can cause overheating of the motor and supply system result in reduction in overall life span of motor, reduced efficiency, poor performance and unwanted failure of drive system causes economic Burdon on organization in form of less production. To solve these issues an attempt is made to make a comparative study on various open loop and close loop drive including PI controller & Fuzzy Logic controller for determination of their advantages and limitations for any particular operation of drive.
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The development of Inverter Fuzzy Logic Control for Induction Motor Control by Vector Control Method in Electric Vehicle

The development of Inverter Fuzzy Logic Control for Induction Motor Control by Vector Control Method in Electric Vehicle

The development of Inverter Fuzzy Logic Control for Induction Motor Control by Vector Control Method in Electric Vehicle. In response to concerns about energy cost, energy dependence, and environmental damage, a rekindling of interest in electric vehicles (EV’s) has been obvious. Thus, the development of power electronics technology for EV’s will take an accelerated pace to fulfill the market needs, regarding with the problem in this paper is presented development of fuzzy logic inverter in induction motor control for electric vehicle propulsion. The Fuzzy logic inverter is developed in this system to directed toward developing an improved propulsion system for electric vehicles applications, the fuzzy logic controller is used for switching process. This paper is describes the design concepts, configuration, controller for inverter fuzzy logic and drive system is developed for this high-performance electric vehicle.
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Speed Control Of Permanent Magnet Synchronous Motor Drive Using Fuzzy Logic Controller

Speed Control Of Permanent Magnet Synchronous Motor Drive Using Fuzzy Logic Controller

Fuzzy logic controller (FLC) solves the problem of nonlinearities and parameter variations of sinusoidal permanent magnet synchronous motor (PMSM) drive. Addition, it can achieves high dynamic performance and accurate speed control with good steady-state characteristics. The control performance can be seen in the MATLAB SIMULINK simulation with various operating with it.

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Speed Control of Single Phase Induction Motor Using Fuzzy Logic Controller

Speed Control of Single Phase Induction Motor Using Fuzzy Logic Controller

Software computing techniques such as fuzzy logic or fuzzy control (FC) provide a schematic method to incorporate human knowledge in the controller [8], it is a control algorithm depends on linguistic control strategy, which is proposed to employ the human experience knowledge to an automatic control strategy. While on the other hand, other control systems employed difficult arithmetic calculation to provide a model of the controlled plant, it only employs simple arithmetic calculation to model this experience. For The good performance of this control strategy, it can be or will be one of the best available answers for a broad class of challenging control problems [9].
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Direct Torque Control of Three Phase Induction Motor Using Fuzzy Logic

Direct Torque Control of Three Phase Induction Motor Using Fuzzy Logic

The DTC scheme is very simple in function; in its basic configuration it consists of hysteresis controllers, torque and flux estimator and a switching table. The basic concept of DTC is to control directly both the stator flux linkage (or rotor flux linkage, or magnetizing flux linkage) and electromagnetic torque of machine simultaneously by the selection of optimum inverter switching modes. The use of a switching table for voltage vector selection provides fast torque response, low inverter switching frequency and low harmonic losses without the complex field orientation by restricting the flux and torque errors within respective flux and torque hysteresis bands with the optimum selection being made. The DTC controller consists of two hysteresis comparator (flux and torque) to select the switching voltage vector in order to maintain flux and torque between upper and lower limit.The DTC scheme of induction motor drive is explained in detail.
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