FUZZY LOGIC BASED DIRECT TORQUE CONTROL OF THREE PHASE INDUCTION MOTOR

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1 Volume 116 No , ISSN: (printed version); ISSN: (on-line version) url: doi: /ijpam.v116i11.18 ijpam.eu FUZZY LOGIC BASED DIRECT TORQUE CONTROL OF THREE PHASE INDUCTION MOTOR 1 Premalatha K and 2 Thirumoorthi P 1,2 Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore - 49 Abstract This paper presents the comparison between three different Direct Torque Control (DTC) strategies for the speed control of Induction Motor (IM): (i) DTC strategy with Hysteresis controllers (ii) DTC-Space Vector Modulation (SVM) with Proportional Integral (PI) controller and (iii) DTC-SVM with Fuzzy Logic controller (FLC). Dynamic behavior as well as steady state behavior of all the three methods is analyzed using MATLAB/SIMULINK. Simulation results show that, the FLC based DTC-SVM gives excellent dynamic and steady state performances. Also DTC SVM gives low torque ripples and maintains the switching frequency constant. Keywords: Direct Torque Control, Space Vector Modulation, Fuzzy Logic Controller, Induction Motor, Torque Ripple Minimization. 1. Introduction Squirrel cage induction motors are used in almost 75% of industrial applications, the popularity of the induction machine is due to its advantages like rugged construction, economical, less maintenance and self-protection against short circuit. Control strategies have indispensable role in high performance of induction motor applications. Predominantly, scalar control and vector control methods are used. Scalar control is simple and easy for implementation. But, the dynamic performance of the IM depends on the machine parameters [1]. DTC has simple calculation and no coordinate transformations. It requires only stator resistance for flux and torque calculation, which diminishes the machine parameter dependency [5, 6]. But conventional DTC 171

2 has some drawbacks; switching frequency of inverter varies with error band and large torque and flux ripples [7].Torque and flux ripples can be reduced by using Multi level inverter (MLI) or DTC-SVM inverter. In this paper three control strategies based on DTC, that can be used for the control of induction motor are described. Comparison between conventional DTC, PI controller based DTC- SVM and Fuzzy controller based DTC-SVM are presented. The fuzzy controller based DTC-SVM gives better result compared to the other methods. 2. Design of PI controller Proportional (Kp) and Integral (Ki) are the two main parameters used for the calculation of change in angle. Proportional constant depends on the present error and Integral time constant depends on the past error. The process can be controlled using weighted sum of these two parameters. The transfer function of PI controller is synthesize as ( ) (26) Figure 1. PI controller based system model PI controller based DTC system can be modelled as shown in fig.1. The performance of PI controller depends on the parameters of Kc and i. 172

3 3. Design of Fuzzy Logic Controller Design of PI controller is quite complicated since it requires accurate mathematical model of the system and also has slower and poor transient responses such as overshoots during dynamic change in torque, oscillation in speed, high settling time and high torque ripple [10-13]. But FLC requires the knowledge of mapping between the inputs and output and it overcomes the drawbacks of PI controller. The Input of FLC is torque error and change in error. Each input and output consists of seven fuzzy sets. Linearized membership corresponding to inputs and output are shown in fig.6. Mamdani min type fuzzy is used for implication and centroid type is used for defuzzification. Fuzzy has seven membership functions for the inputs and an output are Negative Large(NL), Negative Medium(NM),Negative Small(NS),zero(Z), Positive Small(PS), Positive Medium(PM) and Positive Large(PL). Rules used in fuzzy logic controller for the DTC-SVM scheme are listed in Table 1 Table 1. Fuzzy Logic Control Rules NL NM NS ZE PS PM PL * NL NL NL NL NL NM NS ZE NM NL NL NL NM NS ZE PS PM NL NL NM NS ZE PS PM ZE NL NM NS ZE PS PM PL PS NM NS ZE PS PM PL PL PM NS ZE PS PM PL PL PL PL ZE PS PM PL PL PL PL 173

4 Figure 2. Fuzzy membership functions of input & output variables (a) torque error, (b) change in torque error, and (c) output variable. 4. Results And Discussions The methods proposed are modelled and simulated in MATLAB/SIMULINK. Simulations are carried out for different operating conditions such as variable speed and variable torque. The motor parameters are given in appendix. Fig.2 to fig.4 present the responses for load variations of 2 Nm, 4Nm and 3Nm applied at 0.5s, 1s and 1.5s respectively. Reference torque, Electromagnetic torque and d-q axis flux and current waveforms are shown from top to bottom. The Waveforms for the conventional DTC are presented in fig.3. Electromagnetic torque follows the reference torque but the torque ripple is nearly 2.5 Nm. The d and q axis flux waveforms are shown in fig.3d and fig.3e, both waveforms are sinusoidal and 90 degree phase shifted, but the frequency varies randomly with torque changes. Similar to the flux, d and q axis stator current and frequency varies but the current waveform gets distorted and has more ripples. (a) Reference torque 174

5 (b) Estimated torque (c) Stator current (d) Stator flux d axis (e) Stator flux q axis (f) Stator current d axis (a) Stator current q axis 175

6 Figure 3. a) Reference torque b) Electromagnetic torque c) Three phase stator current d) Stator flux d-axis e) Stator flux q- axis f) Stator current d- axis g) Stator current q-axis The waveforms for FLC based DTC-SVM are shown in fig.4. Torque ripples are minimized effectively and transient responses like peak overshoot and rise time also get reduced compared to PI controller based DTC-SVM. The stator current waveform is shown in fig.9c and is sinusoidal, distortion free. The stator current increases with increase in torque. Frequency and peak value of stator current and flux are almost at constant value. (a) Reference torque (b) Estimated torque (c) Stator current (d) Stator flux d axis 176

7 (e) Stator flux q axis (f) Stator current d axis (g) Stator current q axis Figure 4. a) Reference torque b) Electromagnetic torque c) Three phase stator current d) stator flux d-axis flux e) stator flux q-axis flux f) stator current d- axis g) stator current q-axis Table2 shows the rise time and settling time of the PI and Fuzzy controlled DTC-SVM. Comparing the performance of three methods, effective method of controlling of three phase squirrel cage induction motor is FLC based DTC-SVM. This method minimizes the torque ripple, improves the transient and steady state responses. Also, maintains the stator current and flux waveform sinusoidal. TABLE 2. Performance Measures Rise time Settle time PI controller based DTC-SVM s 0.041s Fuzzy Controller based DTC- SVM s 0.035s 5. Conclusion The conventional Direct Torque Control, Direct Torque Control based Space Vector Modulation using PI controller and 177

8 Fuzzy Logic Controller for three phase induction motor has been developed and analysed using MATLAB simulation. Simulations are carried out for dynamic changes in induction motor torque. The simulation results show that DTC-SVM scheme with fuzzy logic controller gives less torque and flux ripples, better transient and steady state response. Also, DTC-SVM maintains the switching frequency constant. References [1] B.K.Bose, Modern Power Electronics and AC Drives, Prentice Hall of India, [2] I.Takahashi, T.Noguchi, A new quick response and high efficiency control strategy of an induction motor, IEEE Transactions on Industrial Applications, Vol.22, No.5, pp , [3] X. Xu, R. DeDoncker, and D. W. Novotny, A stator flux oriented induction machine drive, Power Electronics specialist conference, pp , [4] F. Blaschke, The principle of field-orientation as applied to the trans vector closed-loop control system for rotating-field machines, Siemens Rev, Vol. 34, pp , [5] L.Tang, L.Zhong and M.F Rahman, A novel direct torque controlled interior permanent magnet synchronous machine drive with low ripple in flux and torque and fixed switching frequency, IEEE Transactions on Power Electronics, Vol.19, No.2, pp , [6] M.Bertoluzzo, G.Buja and R. Menis, A Direct Torque Control Scheme for Induction Motor Drives Using the Current Model Flux Estimation, IEEE International Symposium, pp , [7] K.Chikh and M,Khafallah, A novel fixed-switching-frequency DTC for PMSM drive with low torque and flux ripple based on Sinusoidal Pulse with Modulation and predictive controller Multimedia Computing and Systems, International Conference on ICMCS,

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