Majlesi Journal of Electrical Engineering
Volume:6 Issue: 3, Sep 2012

The focus of this study is on developing a framework for a Quantum Algorithm Processing Unit (QAPU) and a hybrid architecture for classical-quantum algorithms. The framework is used to increase the implementation performance of quantum algorithms and design Quantum Processing Units (QPU). The framework shows a general plan for the architecture of quantum processors which is capable to run the quantum algorithms. In particular, the QAPU can be used as a quantum node to design a quantum multicomputer. At first, the hybrid architecture is designed for the quantum algorithms. Then, the relationship between the classical and the quantum part of hybrid algorithms is extracted and main stages of the hybrid algorithm are determined. Next, the framework of the QAPU is designed and developed. Some gates and connections are projected in the framework that can be applied for future quantum algorithms. Furthermore, the framework is implemented and simulated for the existing quantum algorithms on a classic computer. It is shown that the framework is appropriate for quantum algorithms.

Since the search process of the particle swarm optimization (PSO) technique is non-linear and very complicated, it is hard if not impossible, to mathematically model the search process to dynamically adjust the PSO parameters. Thus, already some fuzzy systems had been proposed to control the important structural parameters of basic PSO. But in those researches no effort had been reported for optimizing the structural parameters of the designed fuzzy controller. In this paper a new algorithm called Fuzzy Optimum PSO (FOPSO) has been introduced. FOPSO utilizes two optimized fuzzy systems for optimal controlling the main parameters of basic PSO. Extensive experimental results on many benchmark functions with different dimensions show that the powerfulness and effectiveness of the proposed FOPSO outperforms other version of PSO.

This paper presents a robust control design based on constrained optimization using Differential Evolution (DE). The feedback controller is designed based on state space model of the plant considering structured uncertainty such that the closed-loop system would have maximum stability radius. A wedge region is assigned as a constraint for desired closed loop poles location. The proposed control technique is applied to a two-mass system that is known as benchmark problem for robust control design. The simulation results seem to be interesting in which the robustness performance is achieved in the presence of parameter variations of the plant.

The growing requirement to the clean and renewable energy has led to the rapid development of wind power systems all over the world. With increasing use of wind power in power systems, impact of wind generator on sub-synchronous resonance (SSR) is going to more important. The SSR is a well-known phenomenon in a series compensated power systems which can be mitigated with series or parallel flexible ac transmission systems (FACTS) devices. In this paper wind and steam turbines have been used as a hybrid energy production system. For damping the SSR, thyristor controlled series capacitor (TCSC) as a series FACT devise and unified power flow controller (UPFC) as a series-parallel FACT devise have been used. In order to have an optimal control on pitch angle in high speed of wind, a novel method using imperialist competitive algorithm (ICA) has been used. Also supplementary controllers for UPFC and TCSC have been design and adaptive neuro fuzzy inference system (ANFIS) and fuzzy logic damping controllers (FLDC) are added to these FACTS devises to mitigate the SSR. Finally the results of two FACTS devises have been compared. Also the results obtained from imperialist competitive algorithm (ICA) are compared with PID controller optimized by Particle Swarm Optimization (PSO) algorithm.

This paper analyzes the behavior of a Permanent Magnet Synchronous Generator (PMSG) wind turbine using Maximum Power Extraction (MPE) method in response to wind speed fluctuations. The behavior of the wind turbine in the frequency domain will be analyzed to have the wind turbine response in frequency domain. By combining the wind speed frequency content and wind turbine frequency response, the frequency content of wind turbine output power fluctuation will be gained. A PMSG wind turbine system is simulated with real wind speed data in the PSIM software environment, and the results are compared with theoretical results for validation of the model.

Design and simulation results of fully integrated 5-GHz CMOS LNAs are presented in this paper. Three different input impedance matching techniques are considered. Using a simple L-C network, the parasitic input resistance of a MOSFET is converted to a 50 Ω resistance. As it is analytically proved, that is because the former methods enhance the gain of the LNA by a factor that is inversely proportional to MOSFET’s input resistance. The effect of each input impedance matching on the amplifier’s noise figure and gain is discussed. By employing the folded cascode configuration, these LNAs can operate at a reduced supply voltage and thus lower power consumption. To address the issue of nonlinearity in design of low voltage LNAs, a new linearization technique is employed. As a result, the IIP3 is improved extensively without sacrificing other parameters. These LNAs consume 1.3 mW power under a 0.6 V supply voltage.

This paper incorporates the SSSC FACTS device in optimal power flow solutions to enhance the performance of the power systems. The particle swarm optimization is used for solving the optimal power flow problem for steady-state studies. The effectiveness of the proposed approach was tested on IEEE 14-bus and IEEE 30-bus systems with SSSC FACTS device. Results show that the proposed PSO algorithm gives better solution to enhance the system performance with SSSC device compared to without SSSC device.

The Non-Dimensional star pattern recognition algorithm is known to be independent of image Focal Length and Optical axis offset but this independency doesn’t mean that the algorithm conserves it’s robustness in presence of any type of errors. These errors arise from poor hardware calibration and software inaccuracy which causes the algorithm’s input to be different from the true amount stored in the database. The effect of bright point position errors on pattern feature is modeled. The monte-carlo simulation method is used to evaluate the algorithm’s performance for different amounts of error. Results demonstrate that 0.1 Pixel size error is admissible to conserve the trade-off between valid update frequency, hardware accuracy and algorithm’s robustness.

In this paper, we propose a multiple description video coding system for robust transmission of video signal. We split the video frames into odd and even frames, and encode each frame separately based on JPEG standarad. We assume that each description is transmitted in through WCDMA physical layer. The channel is simulated based on Gilbert/Elliot model. We compare the result in threes cases: Video is reconstructed using only one description; video is reconstructed using both descriptions and finally video is reconstructed based on both description and we do error concealment as well. The video quality is reported based on average peak signal to noise ratio for all cases for a video sequences.