Efficient Direct Torque Control of Induction Motor Based on Fuzzy Logic

Home , AC motor, Direct torque control, Induction motor

Journal of Critical Reviews

ISSN- 2394-5125 Vol 6, Issue 6, 2019

Review Article

EFFICIENT DIRECT TORQUE CONTROL OF INDUCTION MOTOR BASED ON FUZZY LOGIC

T. Jayakumar1, G. Preethi2, V. Sree Sureya3, D. Lavanya4 1Assistant Professor, Department of Electrical and Electronics Engineering, Nandha Engineering College, Erode. [email protected] 2PG Student, Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, Sathyamangalam. [email protected] 3PG Student, Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, Sathyamangalam. [email protected] 4PG Student, Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, Sathyamangalam. lavanya.pe18@ bitsathy.ac.in

Received: 27.11.2019 Revised: 30.12.2019 Accepted: 25.12.2019

Abstract Vector Control Of Induction Motor (IM) is based on dynamic-state relationships. The torque, stator flux and Induction Motor Drive speed will be highly variable under transient and stable operation conditions. From the various induction speed control methods such as pole change, frequency variation, variable rotor resistance, variable stator voltage, constant voltage / frequency control, slip recovery method, etc. Direct Torque Control (DTC) is one of the methods used by Vector Control to control torque and speed of the induction motor. Vector control is better than scalar control because the DTC method can control not only the magnitude but also the position of voltage, currents and flux instantaneously. This method is mainly suggested for controlling torque and speed because of dynamic performance of the induction motor. Thus, high quality of torque, stator flux and rated speed of the Induction Motor (MT) s achieved. Keywords: Direct Torque Control, PI Controller, Fuzzy Logic, Induction Motor, Voltage Source Inverter, PIC Microcontroller.

INTRODUCTION proposed fuzzy logic based controller, speed control of the IN many industrial applications, Adjustable Speed Drives (ASDs) induction motor is carried out. It presents the Induction Motor uses DC motors as controlling element. Due to the disadvantages (IM) DTC scheme and its comparative study using smart of wear and commutating problem, DC motors is nowadays not techniques under different dynamic conditions. The induction preferable. Hence all of the researchers focuses on the control of motor's DTC with a fuzzy controller is discussed in [4]. The aim AC motors. Induction motor can be easily controlled as the speed of this paper is to reduce the stator and the pulsation of and flux depends upon the frequency. The inventions and electromagnetic torque. The principles of the fuzzy controller improvement of power electronics uses silicon devices for fast development for the induction drive with a DTC and the obtained and smooth speed control. For a wide spectrum of industrial computer model were presented. systems, applications of semiconductor devices enhance the automation of the industries. The use of converters for the Soft computing technique-Fuzzy logic is used for induction motor control of IM is of very low cost and size. Speed regulation of IM speed control to ensure maximum torque with minimal loss. is about 3-5%. Even though its speed decreases it is observed as Using the Field Oriented Control technique, the fuzzy logic a constant speed motor. controller is implemented as it offers good motor torque control with better performance. The motor model is designed and Because of their reliability, inexpensive and robustness, membership functions are selected based on the motor model induction motors seem to be the most popularly used electrical parameters[5]. In most nonlinear systems, Artificial Intelligent motors. However, induction motors do not have variable speed has found significant application similar to motor drive. Because operation capability inherently. For this reason, in most electrical artificial intelligent techniques can be used as controller for any drives earlier DC motors were applied .But the recent system without system mathematical model requirement, it's developments in the Induction Motor (IM) speed control been used in electrical drive control. In this way, drive efficiency methods have resulted in their use on almost all electrical drives and reliability increase and decrease their volume, weight and on a large scale. cost [6]. The biggest issue generally associated with the DTC drive is the high torque ripple. Based on fuzzy logic, this problem In[1], paper deals with the Variable-Frequency Drive, an is solved by a torque hysteresis band with variable amplitude. It Adjustable-Speed Drive (ASD) type used in electro-mechanical is shown that, especially at lower speeds, the proposed fuzzy drive systems to manage AC motor speed and torque by differing controller can reduce torque and flux ripples and improve DTC motor input frequency and voltage. It deals with Vector control performance. A smart speed control system based on fuzzy logic valid not only for amplitude but also for instant voltage, currents for indirect induction motor drive controlled by a voltage source and flux positions. In[2], a method was conveyed to improve the PWM inverter-fed vector is presented. The performance of the speed profile of a three-phase induction motor in the DTC drive smart controller was examined through digital simulation using system using a proposed fuzzy logic speed controller. Using the the MATLAB-SIMULINK package for various operating well-known Matlab / Simulink software package, a complete conditions, such as sudden changes in reference speed and load simulation of the conventional DTC and closed-loop for speed torque [8].The speed of IM is directly proportional to the control of three-phase induction motor was tested. In [3], using frequency and inversely proportional to the number of poles. As the conventional proportional integral (PI) controller and the

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EFFICIENT DIRECT TORQUE CONTROL OF INDUCTION MOTOR BASED ON FUZZY LOGIC

it is difficult to control speed by changing number of poles, the highest efficiency at all times. The electromagnetic torque can frequency changing method is commonly adopted. This fact has be expressed as follows in the three phase induction machines. made the use of inverter-fed IM for controlling purpose. In many recent industrial applications, the VSI-fed IM drives are more and more used, requiring excellent transient drive performance[9]. In small workplaces, PI and fuzzy PI controllers are used to reduce Where is the stator flux, is the stator current (both fixed to hazardous indoor air benzene concentrations. A well-mixed the stationary reference frame fixed to the stator) and p is the room model is used to represent the workshop [10]. number of pairs of poles.

The aim of this paper is to develop a model to implement an Main Parts of DTC of Induction Motor induction motor's DTC using Fuzzy logic controller and They are Voltage source inverter and Torque & Flux estimator. modelling of a Voltage Source Inverter (VSI) that drives the induction motor and obtain a waveform showing the relationship a) Voltage Source Inverter (VSI) between speed, torque, current and voltage. An inverter is an electronic device or circuit that convertsDC into AC. The output voltage and frequency depends on the design of DIRECT TORQUE CONTROL WITH PI BASED FUZZY LOGIC the circuit. The inverter does not generate any power, the DC CONTROLLER source provides the power. The inverter has six switches S1 to Induction Motor (IM) Control Methods S6. The output voltage is varied depending on the turn ON/OFF Fig 1 presents a general classification of the methods of variable of switches S1 to S6 and the ac voltage is appeared at the motor frequency IM control. terminals.

b) Torque and Flux Estimator The final torque equation depends on the voltage of the stator, the stator currents and the resistance of the stator phases that can be accurately measured. In fact, there is a significant variation in the stator resistance with time / temperature. The torque and flux equations, especially at low speed, are very sensitive to the resistance. = P ( - ) The stator flux components are given by = ) dt = ) dt Fig:1 General Classifications of Induction Motor Control Method = P( )dt- )dt) Control of speed of IMis very important in industrial and It is necessary to estimate the rotor flux components engineering applications. To reduce operating costs, effective and . control strategies are also used. Induction motors speed control techniques can be widely classified into two types–Scalar Control = and Vector Control. Scalar Control involves controlling the = voltage or induction motor frequency magnitude whereas Vector Control includes instantaneous voltage, currents and flux = positions also. =

Direct Torque Control = The direct torque method controls speed desirably without use of speed sensors. Usually, the flux estimation is based on motor Fuzzy Logic phase voltage integration the integration tend to become Fuzzy logic is a multi-value logic in which the true values of incorrect at low speed due to the inevitable errors in voltage variables can be any real number between 0 and 1, considered measurement and stator resistance estimate. Thus the motor "fuzzy." By contrast, the true values of variables in Boolean logic cannot be controlled if the variable frequency drive output can only be 0 or 1, often referred to as "crisp" values. Fuzzy logic frequency is zero. Fig 2 shows the DTC block diagram. has been extended to deal with the concept of partial truth,

where the value of truth can vary from true to false. In addition, when using linguistic variables, specific (membership) functions can manage these degrees. Fuzzy logic is a technique to incorporate human thinking into a system of control. A fuzzy controller can be designed to recreate empirical human thinking, that is, the process that people use to draw conclusions from what they know. Fuzzy control was applied primarily through fuzzy linguistic descriptions to process control. Fuzzy control system, as shown in Fig 3, consists of four blocks. The process of Fuzzy logic involves Fig:2 Block Diagram of DTC of Induction Motor 1. Fuzzify all input values into functions of fuzzy membership. 2. To calculate the fuzzy output functions, execute all applicable In DTC, Induction Motor Drive is supplied by a voltage source rules in the rule basis inverter. An optimum inverter voltage vector can be selected to 3. To obtain "crisp ' output values, de-fuzzify the fuzzy output functions. directly control the stator flux connection s and the electromagnetic torque Tas. The selection of the voltage vector of the voltage source inverter is very important to limit the error of flux and torque and to achieve the fastest response of torque and

Journal of critical reviews 461

EFFICIENT DIRECT TORQUE CONTROL OF INDUCTION MOTOR BASED ON FUZZY LOGIC

Table:1 Rule based System for Fuzzy Controller

Fig:3 Basic blocks of Fuzzy Logic

PROPOSED FUZZY PI CONTROL DESIGN Fig 4 shows the Fuzzy logic controller scheme.

The Zadeh logical “and” used in the rule-based system for the fuzzy controller is defined as:

µA and µB = min {µA, µB} Fig:4 Scheme of a Fuzzy Logic Controller Where µA and µBare the membership functions of the Fuzzy Sets

A and B, respectively. To get PD, PI and PID fuzzy controllers, a fuzzy controller can be The centroid defuzzifier is used to convert the fuzzy sets to real combined with conventional control. The fuzzy PID control gives numbers. The PI FLC's output change u(t) is given as: proportional output of control from error, error change, and acceleration error. It is known that Fuzzy PI controller is more u (t) = preferable than Fuzzy PD controllers, which have difficulty th Where, hi is the value of the output member for the i rule and µi removing the error in the steady state. It is possible to derive is the output membership value for the ith rule. equation (4) to obtain the PI controller law as

u(t) = kp e(t) + ki Table:2 Fuzzy Control Rule-Base Then, u(t) = kpe(t) + kie(t) Where u(t) is the control signal and e(t) - feedback error. The concentration error (CE) and the change in concentration error (CEC) is obtained by using the gains Ki and Kp from Table 1. Low, medium and high are the three input triangular membership function used in input scaling. Fig5 shows the proposed system.

CE- concentration error;CEC- concentration error change

SIMULATION AND HARDWARE IMPLEMENTATION Simulation Circuit The DTC induction motor simulation circuit based on a PI fuzzy controller is shown in Fig 6.

Fig:5 Proposed Fuzzy PI Control System

The output range of the PI FLC can be set from zero to one. Low, medium and high are the output membership functions. The Mamdani PI FLC can have nine fuzzy control rules based on the Fig:6 Simulation Model features of input and output membership. Table I shows the set of IF-THEN rules used in the rule-based system. The output 5V coming out of the module is passed through the PIC16F877A. The current measurement module is connected across the any two phases of the motor. The port RC0 and RC1 are connected across the current measurement. The current

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EFFICIENT DIRECT TORQUE CONTROL OF INDUCTION MOTOR BASED ON FUZZY LOGIC

values across these two phases are displayed in the LCD display. The PIC microcontroller is programmed by means of fuzzy logic controller and membership function are used to turn on and off the switches. The fuzzy process is used to carry out the function of the module.

Hardware Circuit The port A (RA0) is connected as an input across the voltage measurement. The voltages between any two phases are measured and it is allowed to pass through the potential transformer. The voltage rating is displayed and the Fig:8 Input Waveform to the Bridge Rectifier corresponding current across any two phases are displayed by The output waveform as shown in Fig 9 that comes out of using the current measurement and the LCD display. inverter module is of magnitude 12V. The MOSFET are triggered accordingly to the pulse generated. The port D is considered as the output port, which is connected to the LCD display. The LCD display is of 4 X 4 matrix and it consists of 16 pins. RD 1-RD7 are connected across pin7-14.In the display, pin 2, pin 15 are input I which 5V supply is given .Pin 1 and 5 are grounded. The port B (RB2-RB7) of PIC 16F877A is considered as the output port and it connected to the optocoupler. The 5V supply is passed through the optocoupler and it is allowed to pass through the driver circuit to trigger the MOSFET. A separate power supply module is used to supply the inverter module and 12V supply from the regulator (7812) is passed through the driver circuit. The optocoupler allows the input supply to pass through the driver circuit and the driver circuit is Fig:9 Inverter Output Waveform used to turn on and off the MOSFET according to the switching sequence. The driver circuit is used to trigger the pulse and turn The current measured across the two phases, voltage and speed on the switches. The MOSFT’s are having 1200 phase difference. are displayed. In this, the voltage is set across 100 to 120 Volts. The MOSFET needs separate supply, which is given from the The potentiometer is varied, the torque is varied to 2.23Nm and voltage regulator (7812) and the pulse from the driver circuit is the speed corresponding to the torque is 1200 rpm. Thus, by used to turn on and off the switches sequentially. varying the potentiometer, the torque is adjusted and hence the speed is controlled. The different output by varying the The potentiometer is connected to the pin 1 and the output from potentiometer and corresponding torque and speed are the inverter module is connected across the motor, and by displayed as shown in Fig 10. varying the potentiometer the torque is adjusted through which the speed of the induction motor is controlled. Thus, by varying the potentiometer the torque and speed of the induction motor is controlled.The hardware circuit of the proposed method is shown in Fig 7.

Fig:7 Hardware Model Fig:10 Different Output by Varying the Potentiometer

RESULTS CONCLUSION The module consists of the bridge rectifier, voltage regulator, Thus, the torque is varied by adjusting the potentiometer so that transformer and current measurement, inverter module. The the motor speed is controlled. Based on the speed error, the inverter module comprises of optocoupler, the driver circuit and reference torque is calculated and compared to the estimated the inverter. The waveform passes through the optocoupler and torque and the torque error is passed through the torque then through the driver circuit. The driver circuit magnifies the hysteresis band to check that the error is within the limit. The waveform and it is then passed through the inverter module. The estimated flux is compared with reference flux in the flux inverter module comprises of MOSFET. The MOSFET requires the hysteresis band. The inverter output is varied to control the pulse to trigger them. Henceforth, the input waveform is allowed induction engine based on the selection of flux, torque and to pass and the sequential on and off the MOSFET takes place. voltage vector. The input waveform to the bridge rectifier is shown in the Fig 8. REFERENCES 1. Tejavathu Ramesh, Anup Kumar Panda, Y Suresh and Suresh Mikkili, “Direct Flux and Torque Control of Induction

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