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El-Sousy F.F.M.,Salman bin Abdulaziz University | El-Sousy F.F.M.,Electronics Research Institute of Egypt
IEEE Transactions on Industrial Informatics | Year: 2013

In this paper, an intelligent control system using recurrent wavelet-based Elman neural network (RWENN) for position control of permanent-magnet synchronous motor (PMSM) servo drive is proposed to achieve high precision tracking performance and to deal with the existence of uncertainties. The proposed intelligent optimal RWENN control system (IORWENNCS) incorporating an optimal controller, a RWENN controller and a robust controller. Based on the principle of optimal control, a position tracking controller is designed to minimize a quadratic performance index. In addition, a RWENN controller with accurate approximation capability is used to approximate a nonlinear function in the optimal control law. Moreover, a robust controller with adaptive bound estimation algorithm is proposed to confront the approximation error. The online adaptive control laws are derived based on the optimal control technique and Lyapunov stability analysis, so that the stability of the IORWENNCS can be guaranteed. Using the proposed control scheme, the position tracking performance is substantially improved and the robustness to uncertainties can be obtained as well. All control algorithms are implemented in a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the proposed IORWENNCS grants robust performance and precise tracking response regardless of load disturbances and PMSM uncertainties. © 2005-2012 IEEE.


Attiya A.M.,Electronics Research Institute of Egypt
Applied Computational Electromagnetics Society Journal | Year: 2011

This paper introduces a modal analysis for two-dimensional chiral grating. The grating structure is composed of rectangular chiral rods arranged in rectangular periodic cells and embedded in another chiral base material. Total fields are presented in terms of transverse electric and magnetic field components which are expanded as two sets of TE and TM Floquet modes. This representation is used in Maxwell's curl equations to formulate the problem as an eigenvalue problem. The resulting eigenvalues correspond to the forward and backward propagation coefficients. On the other hand, the eigenvectors correspond to the amplitudes of the TE and TM Floquet modes in the forward and backward propagating modes. Reflection and transmission coefficients of two semi-infinite chiral gratings are obtained by combining this modal analysis and mode matching method. This analysis is extended to obtain the reflection and transmission coefficients of a finite thickness twodimensional chiral grating slab by using the generalized scattering matrix method. © 2011 ACES.


Nafeh A.E.-S.A.,Electronics Research Institute of Egypt
International Journal of Green Energy | Year: 2011

In this paper, a new formulation for optimizing the design of a photovoltaic (PV)-wind hybrid energy home system, incorporating a storage battery, is developed. This formulation is carried out with the purpose of arriving at a selection of the system economical components that can reliably satisfy the load demand. Genetic algorithm (GA) optimization technique is utilized to satisfy two purposes. The first is to minimize the formulated objective function, which is the total cost of the proposed hybrid system. Whereas, the second is to ensure that the load is served according to certain reliability criteria, by maintaining the loss of power supply probability (LPSP) of the system lower than a certain predetermined value. Two computer programs are designed, using MATLAB code in a two M-files, to simulate the proposed hybrid system and to formulate the optimization problem by computing the coefficients of the objective function and the constraints. Also, these two programs are utilized together with the GA tool under MATLAB software to yield the optimum PV, wind, and battery ratings. The results verified that PV-wind hybrid systems feature lower system cost compared to the cases where either PV-alone or wind-alone systems are used. Copyright © Taylor & Francis Group, LLC.


Bayoumi E.H.E.,Electronics Research Institute of Egypt
WSEAS Transactions on Circuits and Systems | Year: 2013

To improve the overall dynamic performance of induction motor in direct torque control (DTC), a novel method of stator resistance estimation based on multi-resolution analysis wavelet PI controller is presented. This estimation method is anchored in an on-line stator resistance correction regarding the variation of the stator current estimation error. The main purpose is to adjust precisely the stator resistance value relatively to the evolution of the stator current estimation error gradient to avoid the drive instability and ensure the tracking of the actual value of the stator resistance. The multi-resolution wavelet controller process the error input with the gains depending on the level of decomposition employed. In order to limit the number of gains, this paper analyzes multi-resolution wavelet controller with a single gain constant. A separate fractional order integrator unit which enhances the controller performance with additional flexibility of tuning and also offers better steady state performance of the motor is introduced. The simulation results show that the proposed method can reduce the torque ripple and current ripple, superior to track the actual value of the stator resistance for different operating conditions.


El-Fayez F.F.M.,Electronics Research Institute of Egypt | El-Fayez F.F.M.,King Saud University
IEEE Transactions on Industrial Electronics | Year: 2010

This paper proposes a hybrid H∞-based wavelet-neural- network (WNN) position tracking controller as a new robust motion-control system for permanent-magnet synchronous motor (PMSM) servo drives. The combinations of both WNN and H∞ controllers would insure the robustness and overcome the uncertainties of the servo drive. The new controller combines the merits of the H∞ control with robust performance and the WNN control (WNNC) which combines the capability of NNs for online learning ability and the capability of wavelet decomposition for identification ability. The online trained WNNC is utilized to predict the uncertain system dynamics to relax the requirement of uncertainty bound in the design of the H ∞ controller. The WNNC generates an adaptive control signal to attain robust performance regardless of parameter uncertainties (PU) and load disturbances. Systematic methodology for both controllers' design is provided. A computer simulation is developed to demonstrate the effectiveness of the proposed WNN-based H∞ controller. An experimental system is established to validate the effectiveness of the drive system. All control algorithms are implemented in a TMS320C31 DSP-based control computer. The simulated and experimental results confirm that the new motion controller grants robust performance and precise dynamic response regardless of load disturbances and PMSM PU. © 2006 IEEE.

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