This paper presents a design and simulation of DC/DC boost converter. This system has a nonlinear dynamic behavior, as it work in switch-mode. Moreover, it is exposed to significant variations which may take this system away from nominal conditions, due to changes on the load or on the line voltage at the input. The input usually is obtained by PV array and therefore the design and simulation in this paper covers the whole range of radiations and temperature. In this paper we analyze the equations of a boost converter and propose a design components and simulation of DC/DC boost converter. This work is applied to photovoltaic system for tracking the point of maximum power.

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This paper presents a linear parameter estimation technique used to estimate the rotor resistance, self inductance of the rotor winding, stator resistance and the stator leakage inductance of an induction motor. Such estimation is important for achieving high estimation performance of induction motor drives. The parameters estimation model expresses the relationships of the dynamic machine model in terms of measurable stator voltages, currents and motor speed. This model is represented by a linear regression equation from which machine parameters can be obtained using a recursive least squares (RLS) estimation algorithm. Simulation results are presented to validate the proposed estimation algorithm with reasonable accuracy of the estimated parameters regardless of load conditions. Comparisons between experimental and calculated steady-state performances using the estimated parameters are also presented.

Objective: This study was to compare the rate of canine retraction with two commercially available straight wire brackets. Materials and methods: A sample of 10 patients with an age range from 15 to 18years, requiring orthodontic treatment. The study was designed clinically (split mouth technique) in the same patient right side bonded by Ormco Roth orthodontic brackets while in the left side were bonded byIMD Roth orthodontic brackets. Canine retraction was measured four times every 28 day till complete retraction of canine occurred. Results: the rate of canine retraction was non significantly different from right and left side, also monthly, weekly and daily rate of canine retraction was non significantly different in the right and left side. Conclusion: The rate of Canine retraction using (IMD brackets is insignificantly different from (Ormco) brackets, both of them have the same rate, during the first ,second, third and fourth interval no significant difference on the rate of canine retraction between the 2 groups

This paper presents the improvement of generation quality for a wind energy conversion scheme using artificial neural network (ANN). High generation quality means that, the induction generator generate voltages and frequency at nominal specified values, under all operating conditions, determined by various wind speeds and loads. The scheme consists of a three-phase induction generator driven by a horizontal axis wind turbine and interfaced to an isolated load. A static VAR compensator (SVC) is connected at the induction generator terminals to regulate its voltage. The mechanical power input is controlled by regulating the blade pitch-angle. Both blade pitch-angle and firing angle are adjusted using an ANN to improve the generation quality for a wind energy conversion scheme. The proposed ANN training is based on suitable values of SVC firing angles and blade pitch-angles of the wind turbine, for achieving a high generation quality at different operating conditions. The training data is obtained by using Newton-Raphson method to generate voltages and frequency at nominal specified values. The simulation results prove that, the wind energy conversion scheme, with the proposed ANN, gives good power generation quality over wide range of wind speeds and loads.