This 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 types of state-space equations using block method for conciliated the accuracy of the results of this method.
The research work represent a fast and simple method for the determination of methionine using chemiluminescence for the methionine-sodium hydroxide-luminol for the generation of a chemiluminesecent derivative of luminal. The emission was measured by continuous flow analysis made sample size of 83µL was used.Response versus concentration extended from 0.2-20 mM.L-1 with a percentage linearity of 96.17% or with 99.17% percentage of linearity for the range 0.6-20 mM.L-1. Reaching to a L.O.D. at (S/N=3) for 5 µM.L-1 from the gradual dilution for the minimum concentration in the calibration graph with a repeatability of less than 0.5% (n=10). A comparison was made between the new developed method with the classical method for the spectrophoto
... Show More<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and optimized extended Kalman filter (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF and EKF depends on the accurate selection of state and noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find the optimal values of state and noise covariance matrices. The main objectives of genetic algorithm to be minimized are the mean square errors (MSE) between actual and estimation of speed, current, and flux. Simulation results show the optimal state and noise covariance matrices can improve the estimation of speed, current, t
... Show MoreThis paper presents L1-adaptive controller for controlling uncertain parameters and time-varying unknown parameters to control the position of a DC servomotor. For the purpose of comparison, the effectiveness of L1-adaptive controller for position control of studied servomotor has been examined and compared with another adaptive controller; Model Reference Adaptive Controller (MRAC). Robustness of both L1-adaptive controller and model reference adaptive controller to different input reference signals and different structures of uncertainty were studied. Three different types of input signals are taken into account; ramp, step and sinusoidal. The L1-adaptive controller ensured uniformly bounded
... Show MoreInformation systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of
... Show MoreRecently, Knowledge Management Systems (KMS) consider one of the major fields of study in educational institutions, caused by the necessity to identify their knowledge value and success. Hence, based on the updated DeLone and McLean’s Information Systems Success Model (DMISSM), this study set out to assess the success of the Perceived Usefulness of Knowledge Management Systems (PUKMS) in Iraqi universities. To achieve this objective, the quantitative method is selected as the research design. In total, 421 university administration staff members from 13 Iraqi private universities were conducted. This study highlights a number of significant results depending on structural equation modeling which confirms that system, information, and s
... Show MoreIn recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.