The systems of governance in Europe are characterized by ancient democratic systems that have developed and developed through a long history of political conflicts that have emerged from a social reality that feeds them and receives the resulting effects. This is an achievement that has been achieved after the sacrifices and great efforts in formulating models of good governance through which to realize the aspirations of their peoples. . The democratic system operates within a balanced mechanism of two competing parties to manage and direct the work of the government and the parliament. The parties that achieve the majority in the elections carry out the functions of the government supported by their parliamentary base belonging to one party or a group of parties that are intertwined within a common intellectual and ideological approach. The parties that did not win the position of opposition in parliament, each according to programs and plans that envisages the right management of the State and what he deems appropriate in the legislation of laws and the exercise of the functions of the government and the required parliamentary oversight to correct and avoid falling into the corners of mismanagement or corruption Which in many cases does not apply to this rule, despite the fact that it represents the basic principle of the democratic approach, namely, the principle of electoral majority, which necessitates the search for another democratic alternative that allows the administration of state affairs, with the participation of political parties In the work of the government and parliament or their consensus, in order to achieve the acceptance of all political parties and then their electoral rules. However, the departure from the rule of the electoral majority has produced new data that have made the system of consensus democracy in general its specificity as it is achieved
This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat
... Show MoreThis paper presents a newly developed method with new algorithms to find the numerical solution of nth-order state-space equations (SSE) of linear continuous-time control system by using block method. The algorithms have been written in Matlab language. The state-space equation is the modern representation to the analysis of continuous-time system. It was treated numerically to the single-input-single-output (SISO) systems as well as multiple-input-multiple-output (MIMO) systems by using fourth-order-six-steps block method. We show that it is possible to find the output values of the state-space method using block method. Comparison between the numerical and exact results has been given for some numerical examples for solving different type
... Show MoreThis paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MoreThe evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
... Show MoreA theoretical study has been proposed to investigate the effects of different laser radiations (Nd - glass, DF and C02) as a heating source on different glass samples (Optical glass, Bk - 7 and Soda - lime glass) and different waves lengths (10.6, 3.8, 1.6) ???. The heat changes as which are resulted due irradiation with laser sources have been determined by using the one dimension mathematical relation as a function of time (t) and depth (z). The results of the study show ed that the irradiation with C02 laser had a greater effect than DF laser, while the effects of Nd - glass laser were minimal with a power density of (1.8*10?? w/m2) within atime(l^sec).(Forboth Kinds) The change in the temperatures were not exceeded than (70"K) in all sa
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