Iranian Journal of Electrical and Electronic Engineering

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The main theme of this paper is to present novel controller, which is a genetic based fuzzy Logic controller, for interior permanent magnet synchronous motor drives with direct torque control. A radial basis function network has been used for online tuning of the genetic based fuzzy logic controller. Initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition, a genetic algorithm is used to optimize fuzzy logic parameters in closed-loop direct torque control scheme. In other words, the genetic algorithm finds optimum input and output scaling factors and optimum number of membership functions. This optimization procedure is utilized to obtain the minimum speed deviation, minimum settling time, zero steady-state error. The control scheme has been verified by simulation tests with a prototype interior permanent magnet synchronous motor.

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A switched Reluctance motor (SRM) has several desirable features, including simple construction, high reliability and low cost. However, it suffers from large torque ripple, highly non-uniform torque output and magnetization characteristics and large noise. Several studies have succeeded in torque ripple reduction for SRM using Direct Torque Control (DTC) technique. DTC method has many advantages over conventional voltage control and current chopping mode control such as simple algorithm, less torque ripple and instantaneous response to the torque command. In this paper, DTC method is proposed for a 5-phase 10/8 SRM. The performance of the motor is demonstrated through the computer simulation in Mtalab/Simulink. Then, the obtained results are verified by comparison with the corresponding results of a 3-phase 6/4 motor performance.

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Here, a new fuzzy direct torque control algorithm for induction motors is proposed. As in the classical direct torque control, the inverter gate control signals directly come from the optimum switching voltage vector look-up table, the best voltage space vector selection is a key factor to obtain minimum torque and flux ripples. In the proposed approach, the best voltage space vector is selected using a new fuzzy method. A simulation model is built up and the torque and flux ripples of basic direct torque control and the proposed method are compared. The simulation results show that the torque and flux ripples are significantly decreased and in addition, the switching frequency can be fixed.

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This paper presents a comparative study on the Predictive Direct Torque Control method and the Indirect Space Vector Modulation Direct Torque Control method for a Doubly-Fed Induction Machine (DFIM) which its rotor is fed by an Indirect Matrix Converter (IMC). In Conventional DTC technique, good transient and steady-state performances are achieved but it presents a non constant switching frequency behavior and non desirable torque ripples. However, in this paper by using the proposed methods, a fixed switching frequency is obtained. In this model Doubly-Fed Induction Machine is connected to the grid by the stator and the rotor is fed by an Indirect Matrix Converter. Functionally this converter is very similar to the Direct Matrix Converter, but it has separate line and load bridges. In the inverter stage, the Predictive method and ISVM method are employed. In the rectifier stage, in order to reduce losses caused by snubber circuits, the rectifier fourstep commutation method is employed. A comparative study between the Predictive DTC and ISVM-DTC is performed by simulating these control systems in MATLAB/SIMULINK software environments and the obtained results are presented and verified.

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