Direct Torque Control of Induction Machine based on Intelligent Techniques
Soufien Gdaim, Abdellatif Mtibaa, Mohamed Faouzi Mimouni
Abstract
Soufien Gdaim, Abdellatif Mtibaa, Mohamed Faouzi Mimouni
Abstract
Induction machine drive based on Direct Torque Control (DTC) allows high dynamic performance with very simple hysteresis control scheme. Conventional Direct Torque Control (CDTC) suffers from some drawbacks such as high current, flux and torque ripple, difficulties in torque as well as flux control at very low speed. In this paper, we propose two intelligent approaches to improve the direct torque control of induction machine; fuzzy logic control and artificial neural networks control. We carry out a detailed comparison study between direct torque fuzzy control (DTFC), direct torque neural networks control (DTNNC) and CDTC applied to switching select voltage vector. The theoretical foundation principle, the numerical simulation procedure and the performances of both methods are also presented.
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Induction machine drive based on Direct Torque Control (DTC) allows high dynamic performance with very simple hysteresis control scheme. Conventional Direct Torque Control (CDTC) suffers from some drawbacks such as high current, flux and torque ripple, difficulties in torque as well as flux control at very low speed. In this paper, we propose two intelligent approaches to improve the direct torque control of induction machine; fuzzy logic control and artificial neural networks control. We carry out a detailed comparison study between direct torque fuzzy control (DTFC), direct torque neural networks control (DTNNC) and CDTC applied to switching select voltage vector. The theoretical foundation principle, the numerical simulation procedure and the performances of both methods are also presented.
Key concepts: Direct torque control, Torque, Computer science, Torque ripple, Control theory (sociology), Vector control, Fuzzy logic, Artificial neural network