In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is applied to learn the control structure for self-tuning PID type neuro-controller. Where the neural network is used to minimize the error function by adjusting the PID gains. Simulation results show that the self-tuning PID scheme can deal with a large unknown nonlinearity
The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.
The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost, loss etc. while maintaining an acceptable system performance in terms of limits on generators real and reactive powers, line flow limits etc. The OPF solution includes an objective function. A common objective function concerns the active power generation cost. A Linear programming method is proposed to solve the OPF problem. The Linear Programming (LP) approach transforms the nonlinear optimization problem into an iterative algorithm that in each iteration solves a linear optimization problem resulting from linearization both the objective function and constrains. A computer program, written in MATLAB environme
... Show MoreIn this paper the use of a circular array antenna with adaptive system in conjunction with modified Linearly Constrained Minimum Variance Beam forming (LCMVB) algorithm is proposed to meet the requirement of Angle of Arrival (AOA) estimation in 2-D as well as the Signal to Noise Ratio (SNR) of estimated sources (Three Dimensional 3-D estimation), rather than interference cancelation as it is used for. The proposed system was simulated, tested and compared with the modified Multiple Signal Classification (MUSIC) technique for 2-D estimation. The results show the system has exhibited astonishing results for simultaneously estimating 3-D parameters with accuracy approximately equivalent to the MUSIC technique (for estimating elevation and a
... Show MoreThe current research tackles the self-efficacy and its relation to the cognitive assessment for the daily disturbances for the University of Baghdad students. Two criteria have been adopted to achieve the objectives of the research. The sample of this study consists of 200 male and female students who were chosen randomly. The data were analyzed statistically, revealing that the university students owned their own self-efficacy as well as a cognitive assessment for the daily disturbances and they recognized them as self-threatening. The results also indicated the existence of a prediction activity in the field of the cognitive assessment to the daily disturbances selection. In light of the acquired results, the study recommends the neces
... Show MoreThis paper presents the design of a longitudinal controller for an autonomous unmanned aerial vehicle (UAV). This paper proposed the dual loop (inner-outer loop) control based on the intelligent algorithm. The inner feedback loop controller is a Linear Quadratic Regulator (LQR) to provide robust (adaptive) stability. In contrast, the outer loop controller is based on Fuzzy-PID (Proportional, Integral, and Derivative) algorithm to provide reference signal tracking. The proposed dual controller is to control the position (altitude) and velocity (airspeed) of an aircraft. An adaptive Unscented Kalman Filter (AUKF) is employed to track the reference signal and is decreased the Gaussian noise. The mathematical model of aircraft
... Show MoreMost of the studies conducted in the past decades focused on the effect of interest rates and exchange rates on domestic investment under the assumption that the independent variables have the same effect on the dependent variable, but there were limited studies that investigated the unequal effects of changes in interest rates and exchange rates, both positive and negative, on domestic investment. This study used a nonlinear autoregressive distributed lag (NARDL) model to assess the unequal effects of the real interest rate and real exchange rate variables on domestic investment in Egypt for the period 1976 - 2020. The results revealed that positive and negative shocks for both exchange rates have unequal effects on
... Show MoreThis study aims to investigate the behavior and strength of self-compacted ferrocement slabs under punching shear load. Experimental results of thirteen square ferrocement slabs of 500×500 mm simply supported on all edges are presented. The main parameters investigated include the volume fraction of reinforcement, slab thickness and size of load-bearing plate. The load deflection and cracking characteristics of the tested slabs are studied and compared. The test results showed that the volume fraction of wire mesh has significant effect on both ultimate load and displacement. The increase of slab thickness leads to decrease in deflection values and increase in stiffness of slabs. Both ductility and stiffness increase as the
... Show MoreIn this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.