A High Performance Induction Motor Drive System Using Fuzzy Logic Controller

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A HIGH PERFORMANCE INDUCTION MOTOR DRIVE SYSTEM USING FUZZY LOGIC CONTROLLER

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VIGNAN’S ENGINEERING COLLEGE

VADLAMUDI

A HIGH PERFORMANCE INDUCTION MOTOR DRIVE SYSTEM USING FUZZY LOGIC CONTROLLER

ABSTRACT

Abstract- Basically, the motor drive system comprises a voltage source inverter-fed induction motor (VSIM): namely a three-phase voltage source inverter and the induction motor. The squirrel-cage induction motor voltage equations are based on an orthogonal d-q reference-rotating frame where the coordinates rotate with the controlled source frequency. The paper presents a novel fuzzy logic controller for high performance induction motor drive system. The inputs to the fuzzy logic controller are the linguistic variables of speed error and change of speed error, while the output is change in switching control frequency of the voltage source inverter. In this paper a comparison between fuzzy logic controller and traditional PI controllers are presented. The results validate the robustness and effectiveness of the proposed fuzzy logic controller for high performance of induction motor drive. Simulink software that comes along with MATLAB was used to simulate the proposed model.

I. INTRODUCTION

Simulink induction machine models are available in the literature [1-2], but they appear to be black boxes with no internal details. Some of them in [1-2] recommend using S functions, which are software source codes for Simulink blocks. This technique does not fully utilize the power and ease of 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 novel fuzzy logic controller suitable for speed control of induction motor drives.

II. SIMULINK IMPLEMENTATION

One of the most popular induction motor models derived from this equivalent circuit is Krause's model [6]. An induction machine model can be represented with five differential equations. To solve these equations, they have to be rearranged in the state-space. form, X=Ax+b Where X=[Fqs FdsFdr Fdr (r] T is the state vector.

The inputs of a squirrel cage induction machine are the three-phase voltages, their fundamental frequency, and the load torque. The outputs, on the other hand, are the three phase currents, the electrical torque, and the rotor speed. The d-q model requires that all the three-phase variables have to be transformed to the two-phase synchronously rotating frame. Consequently, the induction machine model will have blocks transforming the three-phase voltages to the d-q frame and the d-q currents back to three-phase. The induction machine model implemented in this paper is shown in Fig. I. It consists of five major blocks: the o-n conversion, abc-syn conversion, syn-abc conversion, unit vector calculation, and the induction machine d-q model...
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