Showing 3 results for Arab Khaburi
D. Arab Khaburi, H. Rostami,
Volume 7, Issue 1 (March 2011)
Abstract
This paper presents a method to control both the dc boost and the ac output voltage of Z-source inverter using neural network controllers. The capacitor voltage of Z-source network has been controlled linearly in order to improve the transient response of the dc boost control of the Z-source inverter. The peak value of the line to line ac output voltage is used to control and keep the ac output at its desired value. A modified space vector pulse-width-modulation method is also applied to control the shoot-through duty ratio for boosting dc voltage. This modified method lets the dc voltage stress across the inverter switches be minimized. The neural network control technique is verified by simulation results. The results are compared with that of the traditional PI controller.
D. Arab Khaburi,
Volume 8, Issue 2 (June 2012)
Abstract
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.
S. Heshmatian, D. Arab Khaburi, M. Khosravi, A. Kazemi,
Volume 14, Issue 1 (March 2018)
Abstract
Wind energy is one of the most promising renewable energy resources. Due to instantaneous variations of the wind speed, an appropriate Maximum Power Point Tracking (MPPT) method is necessary for maximizing the captured energy from the wind at different speeds. The most commonly used MPPT algorithms are Tip Speed Ratio (TSR), Power Signal Feedback (PSF), Optimal Torque Control (OTC) and Hill Climbing Search (HCS). Each of these algorithms has some advantages and also some major drawbacks. In this paper, a novel hybrid MPPT algorithm is proposed which modifies the conventional methods in a way that eliminates their drawbacks and yields an improved performance. This proposed algorithm is faster in tracking the maximum power point and provides a more accurate response with lower steady state error. Moreover, it presents a great performance under conditions with intensive wind speed variations. The studied Wind Energy Conversion System (WECS) consists of a Permanent Magnet Synchronous Generator (PMSG) connected to the dc link through a Pulse-Width Modulated (PWM) rectifier. The proposed algorithm and the conventional methods are applied to this WECS and their performances are compared using the simulation results. These results approve the satisfactory performance of the proposed algorithm and its notable advantages over the conventional methods.
