A common method for Controlling a group of parallel converters in decentralized Control strategy structure in an island microgrid, the use is the droop-down characteristics of frequency ω-P and voltage E-Q. However, the problem with using this method is that the reactive power is not properly distributed (in proportion to the capacity of the micronutrients) between the micronutrients, which may lead to overload in the converters. Microgrids may also suffer from dynamic stability problems such as power fluctuations, which can be increased by switching between active and reactive power Control. To avoid this problem, the X / R ratio of transmission lines is an important parameter that should be carefully considered in the design of micronutrient Controllers. By linearizing and simplifying conditions, the Control system conversion function model becomes a single input-single output system, which is efficient enough to show the relationship between Control parameters such as slope of droop characteristics and derivative sentences, virtual impedance, and voltage Controllers. Using this model, stability conditions for different parameters are analyzed. Also, to improve power distribution stability, common droop strategies are modified by adjusting the slope as well as adding nonlinear sentence sections. This approach reduces the coupling between active and reactive power Control and reduces the dependence of power distribution on grid parameters such as the X / R ratio. To evaluate the reliability of the proposed model, the simulation results in a sample island microgrid in MATLAB software are presented.

In recent decades , the vibration Control of the structures subject to some loads , such as winds and earthquakes , etc . , has been widely expressed. Vibration Control, which intends to keep the behavior of a structure within a permissible limit , is utilized in several structures , like bridges , tall buildings , wind turbines , foundations with additional vibrations in industry , and even ordinary structures. In this paper , some of the recent studies on optimal Control of the structures are reviewed. In other words , a comprehensive review of articles on the optimal design of different known Control systems of each category i.e. , Tuned Mass Dampers (Active , Passive , and Semi - active) , Viscoelastic Dampers and Base Isolation (Passive and Semi - active) , Fluid Viscous Dampers (Passive and Semi - active) and the active Tendons , with special attention to studies performed in the past decades, are presented. Also , due to simplicity , reliability , and maximum energy dissipation of the friction dampers as an energy dissipation device , especially for seismic amplification of the engineering structures , a brief overview of the optimization of the friction dampers is discussed.

In this paper a semi-active Structural damage Control strategy using MR dampers and Neural Networks is presented. A multilayer feed-forward neural network has been designed. The input layer is relative displacement of stories and the output layer is the voltage needed for MR damper. The neural network is learned to predict the voltage needed for MR damper that can minimize the Park & Ang damage index of structure. Genetic algorithm has been used to learn the neural network. The Park & Ang damage index of the structure has been used as the fittnees function of the genetic algorithm. To evaluate the Structural Control system a nonlinear 3 story benchmark building has been selected. The results show the the proposed Structural Control system can effectively reduce the Park & Ang damage index of the structure.

When designing new civil, mechanical or aerospace systems that will experience dynamic excitation in their operating environment, it is desirable to quantify the predicted performance of a proposed design in terms of the reliability that it will achieve the specified design objectives. In view of the uncertainties about the modeling of systems and about the future dynamic excitation the system will experience, the design team can specify a set of possible dynamic inputs and a set of possible models of the system and then choose probability distributions over these sets to model the uncertainties. One can then evaluate the ‘ failure probability’ of the design that measures how likely the system will achieve the desired performance over its operational lifetime, based on available information and the probability models chosen to represent the missing information. Because of the uncertainty inherent in engineering structures, consistent probabilistic stability/performance measures are essential to accurately assessing and comparing the robustness of Structural Control systems. Several reliability estimation methods, procedures and algorithms with various capabilities, accuracy and efficiency have been suggested in the past. A quantitative comparison of these approaches is considered to be most instrumental and useful for the engineering community. An approach is presented herein for calculating such probabilistic measures for a Controlled structure. Subset Simulation method is shown to be appropriate for the required calculations. The original version of Subset Simulation, SubSim/MCMC, employs a Markov chain Monte Carlo (MCMC) method to simulate samples conditional on intermediate failure events it is a general method that is applicable to all the benchmark problems. The concepts are illustrated through several examples of seismically excited structures with active protective systems. The results show that the original version of Subset Simulation based on the Metropolis– Hasting algorithm is robust and efficient in estimating the probability of failure of Structural systems with complex failure regions, large numbers of random variables, and small probabilities of failure. and applicable to all problems.

Competition law is a newcomer to the legal system recently. A sound understanding of competition policy can provide us with sufficient bases to apply a fundamental and normative view of the issues of competition law. The difference in supervision and regulation determines how the market functions and in order to understand this difference one must understand competition policy. Competition policy may be based on governmental support for national production and industry or on a non-interventional and regulatory posture. Moreover, supervision, based on the principle of non-intervention in the market mechanism, is rooted in liberal ideas; however, regulation, whether as a rule or an exception, is based on the assertion that the market has been ineffective in attaining its goals. Therefore, the government will resort to interventions to regulate inefficiencies.  This paper aims to analyze Supervisory Authority in Implementing Competitive Policy by employing the description method. In this article the author tries to first delineate competition policy, its related requirements and imposed deviations to the market. Then, by defining the supervisory entity and clarifying its distinction from the regulatory institutions, the author considers the characteristics of an appropriate supervisory entity conducting a comparative study of this issue in Iran and the U.S.A. This form of Competition policy because of its applicable experiences which have been well described by recent scholarship is considered suitable for the native system.