Sharif Digital Repository

In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noise-corrupted value of function at any chosen point in the parameter space is available. We first introduce a new continuous action-set learning automaton (CALA) and study its convergence properties. Then we give an algorithm for optimizing an unknown function. © 2005 The Franklin Institute. Published by Elsevier Ltd. All rights reserved  

Paralleling power modules is designed to share system loads (stresses) equally to improve system reliability. Due to variations in the parameters in the power converter system, temperature mismatches may occur. These mismatches may lead to unequal life expectancy of individual converters in the total system. It is believed that equalizing the operating temperature of the semiconductor devices may improve total system reliability. In this paper a new thermal-based load-sharing scheme for parallel converters is proposed. In this scheme, the load current is redistributed among parallel converters based on the temperature of the converters. The main goal is to minimize the relative temperature... 

In this paper, AC Optimal Power Flow combined with UPFC has been used to manage the congestion of transmission lines in a restructured power system with pool market model. The modeling of Unified Power Flow Controller (UPFC) has been adopted based on bipolar model and power injection method. To determine an appropriate location for UPFC as well as to set its parameters, an approach based on genetic algorithm has been suggested. The modified IEEE 14-bus system is used to determine the effectiveness and applicability of the proposed method and results are discussed. ©2006 IEEE  

The well-known ant colony optimization meta-heuristic is applied to design a new command to line-of-sight guidance law. In this regard, the lately developed continuous ant colony system is used to optimize the parameters of a pre-constructed fuzzy sliding mode controller. The performance of the resulting guidance law is evaluated at different engagement scenarios. © Springer-Verlag Berlin Heidelberg 2005  

Dynamic stability of machine tools during operations is dependent on many parameters including the spindle speed. In high and ultra high speed machining, the gyroscopic on the spindle dynamics becomes more pronounced and can affect the borders of stability of the rotating system. In this paper, a finite element based model of spindle, tool holder and cutting tool based on Timoshenko beam theory is used to obtain the dynamic response of the system when gyroscopic terms are included. An iterative scheme is used to update the speed dependent frequency response of the system for obtaining system stability characteristics. It is shown that the gyroscopic effect reduces the critical depth of cut... 

This article presents an overview of the mechanical design and fabrication of a Rescue Robot (CEDRA) for operation in unstructured environments. In order to obtain an appropriate mechanism for climbing the stairs, a novel method has been developed. In this kinematics-based approach we don't need to perform any dynamic analysis which is highly complicated and time consuming for most rovers. According to the essential characteristics needed for rovers, two objective functions were defined. We have shown that the new mechanism performs better on rough terrains than the previous well-known mechanism widely used in the Mars rovers. Moreover the design parameters are optimized by means of Genetic... 

Motion blur is one of the most common blurs that degrades images. Restoration of such images are highly dependent to estimation of motion blur parameters. Many researchers since 1976 have developed algorithms to estimate linear motion blur parameters. These algorithms are different in their performance, time complexity, precision and their robustness in noisy environments. In this paper we have presented a novel algorithm to estimate linear motion blur parameters such as direction and extend by using Radon transform to find direction and power spectrum modeling to find its extend. The most benefit of this algorithm is its robustness and precision in noisy images. This algorithm is a... 

Transferring image sequences requires a very high bit-rate on the communication channels. However, if we want to use telephone lines as the means of communication, the bandwidth constraint problems limit the bit-rates, and the optimal exploitation of link and resource are required. The statistical analysis of video signals indicates that there is a strong correlation both between successive picture frames as well as within the picture elements themselves. Theoretically, decorrelation of these signals can lead to bandwidth compression without significantly affecting image resolution. In this research, in order to reduce bit-rate, we propose a new algorithm using Bilinear Transformation... 

A set of conventional feedforward multilayer neural networks have been proposed to predict basic properties (e.g., critical temperature (T c), critical pressure (Pc), critical volume (V c), acentric factor (ω) and molecular weight (MW)) of pure compounds and petroleum fractions based on their normal boiling point (T b) and liquid density at 293 K. The accuracy of the method is evaluated by its application for basic property estimation of various components not used in the development of the method. Furthermore, the performance of the method is compared against the performance of the other alternatives reported as the most accurate and general methods for basic property prediction. Results of... 

The ARMA filtered fractionally differenced Gaussian Noise (FdGn) model and a new AR Filtered FdGn Added up model are applied to speech signal and performance of their parameters on speech Unvoiced/Voiced/Mixed/Silence classification is evaluated against Zero Crossing Rate (ZCR) feature. For parameter estimation of AR filtered FdGn model two methods were applied: iterative Maximum Likelihood (ML) method of Tewfik and a new computationally efficient Linear Minimum Square Error (LMSE) algorithm Also for parameters estimation of new Added up model two approaches were implemented: an Expectation-Maximization (EM) based approach and an iterative MSE approach. The described models and methods were... 

The reliability analysis of critical systems is often performed using fault-tree analysis. Fault trees are analyzed using analytic approaches or Monte Carlo simulation. The usage of the analytic approaches is limited in few models and certain kinds of distributions. In contrast to the analytic approaches, Monte Carlo simulation can be broadly used. However, Monte Carlo simulation is time-consuming because of the intensive computations. This is because an extremely large number of simulated samples may be needed to estimate the reliability parameters at a high level of confidence. In this paper, a tree model, called Time-to-Failure tree, has been presented, which can be used to accelerate the... 

Implementation of local quantum gate on specific qubits in an array of qubits by carrying a Hamiltonian around a closed loop is discussed. A family of isospectral Hamiltonians with the same spectrum of the projection operator on the main array is constructed by choice of a suitable curve. For every single qubit gate acting on the k-th qubit, a local operator Xk acts nontrivially on the ancilla and the qubit. Imbedding appropriate operators for a suitable set of qubit gates comprises of a universal set of quantum gates. In tensor product of the array one can enact holonomically any set of gates on any subset of qubits  

The concept of Shape Memory Alloy (SMA) has been a subject of extensive research in the recent few years. In many SMA applications, wire elements have been used in order to control structural specifications like shape and stiffness. Since a wire can only be subjected to tensile forces, the available theoretical models for SMA discuss only the tensile loading. The present paper is an endeavor to overcome this shortcoming. It gives experimental results for tension and compression tests on specimens (having different geometries) made of an identical shape memory alloy. The corresponding results are compared with each other. Using stress-strain diagrams, several important material properties are... 

An application of the multiple models adaptive control based on switching and tuning to a flexible transmission system will be presented. This approach has been considered in order to assure high control performance in the presence of large load variation on the system. The advantages of the multiple models adaptive control system with respect to the classical adaptive control will be illustrated via the experimental results. It will also be shown that the robustness of the adaptive control system can be improved with the appropriate shaping of a sensitivity function. The use of a recently developed parameter estimation algorithm based on the minimization of the closed-loop output error in... 

This paper addresses the problem of robust parameter estimation of simple linear profiles in multistage processes in the presence of outliers in Phase I. In this regard, two robust approaches, namely the Huber’s M-estimator and the MM estimator, are proposed to estimate the parameters of the process in Phase I in the presence of outliers in historical data. In addition, the U statistic is applied to the robust parameter estimates to remove the effect of the cascade property in multistage processes and as a result, to obtain adjusted robust estimates of the parameters of simple linear profiles. The performance of the proposed methods is evaluated under weak and strong autocorrelations... 

In this paper, We develop concurrent learning adaptive controller, which uses recorded and current data concurrently for adaptation, to model reference adaptive control (MRAC) of uncertain switched nonlinear systems. In standard MRAC architecture for switched systems, the adaptive update laws are derived based on the gradient descent scheme, but here we developed two novel parameter estimation schemes by using modification terms in adaptation laws in which recorded data are used simultaneously with current data and a triggering time is considered in which a sufficient condition on the linear independence of the recorded data is obtained to guarantee the exponential convergence of tracking... 

In this paper, We propose concurrent learning adaptive controller, which uses recorded and current data concurrently for adaptation, to model reference adaptive control (MRAC) of uncertain switched systems. In standard MRAC architecture for switched systems, the adaptive update laws are derived based on the gradient descent scheme, but here we developed two novel parameter estimation schemes by using modification terms in adaptation laws in which recorded data is used simultaneously with current data and a triggering time is considered in which a sufficient condition on the linear independence of the recorded data is obtained to guarantee the exponential convergence of tracking error and...