Abstract:The DTC-SVPWM scheme is a kind of high performance control scheme of induction motor drives to improve the high torque ripple drawback of conventional DTC. SVPWM has two PI controllers which are used to generate the reference stator voltage vector. However it is difficult to adjust the parameters of PI controller due to the complexity of the control system. The self-tuning PI fuzzy controller was proposed to adjust the PI parameters in this paper. Two inputs of the fuzzy controller are torque or flux error and error change rate. Correction coefficients of proportional and integral are outputs. The simulation results show that the proposed method can significantly reduce the torque ripple and is suitable for various motor at different working state.Key words: DTC, fuzzy controllers, induction motor drive, SVPWM.
IntroductionAmong all control methods for induction motor drives (IMD), direct torque control seems to be particularly interesting being independent of machine rotor parameters. In the last years DTC has become a popular technique for three-phase IMD as it provides a fast dynamic torque response and robustness under machine parameter variations without the use of current regulators [1]- [3]. The major disadvantage of the DTC drive is the steady state ripples in torque and flux [4]. A torque ripple analysis since none of the inverter switching vectors is able to generate the exact stator voltage required to produce the desired changes in torque and flux, torque and flux ripples compose a real problem in DTC induction motor drive [5]. The most common solution to this problem is to use space vector modulation depends on the reference torque and flux. In DTC-SVPWM, the PI controllers substitute by the hysterics comparators [6]. A fast torque response with low torque ripple for this SVM-DTC is significantly improved with a constant switching frequency compare to classical DTC In [7] proposes a neuro-fuzzy based SVM technique for voltage source inverter and its performance is compared with the conventional based SVM and Neural Network based SVM methods. This scheme is five-layer network, receives the d-axis and q-axis voltages information at the input side and generates the duty ratios as an output for the inverter circuit. In [8] the fuzzy PI speed controller has a better response for a wide range of motor speed. In [9] it is designed a Takagi-Sugeno fuzzy controller to substitute flux and torque PI controllers in a conventional DTC-SVM scheme. Flux error after fuzzy controller generates d axis component of the reference voltage vector, torque error after PI regulator generates q axis component of the reference voltage vector, fuzzy control is widely used in direct torque control system, and the superiority of its robust has been showed in [10].
International Journal of Computer and Communication Engineering
204Volume 4, Number 3, May 2015Three-Phase Induction Motor DTC-SVPWM Scheme with Self-tuning PI-Type Fuzzy ControllerIn this paper an adaptive fuzzy PI controller along with the SVPWM technique is...