This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used as a strong approximator for estimation of uncertainty. The designed control law includes three terms: a feedforward term, a feedback term and a robust term for compensation of modeling error. Lyapunov stability is used to prove the validity of the proposed controller and to derive the update laws for the weighting vectors of orthogonal Chebyshev approximators. A case study of a geared DC motor in connection with a rotating output load is simulated to prove the effectiveness of the proposed controller structure.
Experimental tests were conducted to investigate the thermal performance (cooling effect) of water mist system consisting of 5μm volume median diameter droplets in reducing the heat gain entering a room through the roof and the west wall by reducing the outside surface temperature due to the evaporative cooling effect during the hot dry summer of Baghdad/Iraq. The test period
was Fifty one days during the months May, June, and July 2012. The single test day consists of 16 test hours starting from 8:00 am to 12:00 pm. The results showed a reduction range of 1.71 to 15.5℃ of the roof outside surface temperature and 21.3 to 76.6% reduction in the daily heat flux entering the room through the roof compared with the case of not using w
The objective of this research was to investigate the effect of replacing fat(shortening) with different percentages of tahena on the quality properties (physiochemical and sensory ) of shortened cake.The percentages of moisture,protein ,fat and ash of cake increased significantly(p<0.05) as the replacement was increased .The highest increase percentages were 10,48,5,and 90 %,respectivly, at 100% replacement .Carbohydrate,however,decreased by 10%at 100% replacement .these findings may indicate improvement of cake nutritional value.Standing height,as an indicator of cake volume, also increased significantly by 4% at the 50% replacement then it decreased by 4% 100% replacement level. Basic formula (control) has signific
... Show MoreMultilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d
Background: Aesthetic archwires are used to overcome the aesthetic problems of stainless steel wires but the color of the coating layer can be changed with time when exposed to oral environments. The aim of this study was to evaluate the degree of color change of different aesthetic archwires from different companies under different coloring solutions. Materials and Methods: One hundred fifty samples of coated archwires from three companies (Highland, G&H and Dany) were immersed in 5 solutions (artificial saliva, turmeric, tea, coffee and Miranda) to evaluate the degree of color changes after 7, 14 and 21 days using visible spectrophotometer. Data were collected and analyzed using one way ANOVA and post hoc Tukey’s tests. Resu
... Show MoreThe world is currently facing a medical crisis. The epidemic has affected millions of people around the world since its appearance. This situation needs an urgent solution. Most countries have used different solutions to stop the spread of the epidemic. The World Health Organization has imposed some rules that people should adhere. The rules are such, wearing masks, quarantining infected people and social distancing. Social distancing is one of the most important solutions that have given good results to confront the emerging virus. Several systems have been developed that use artificial intelligence and deep learning to track social distancing. In this study, a system based on deep learning has been proposed. The system includes monitor
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The aim of this work is to create a power control system for wind turbines based on fuzzy logic. Three power control loop was considered including: changing the pitch angle of the blade, changing the length of the blade and turning the nacelle. The stochastic law was given for changes and instant inaccurate assessment of wind conditions changes. Two different algorithms were used for fuzzy inference in the control loop, the Mamdani and Larsen algorithms. These two different algorithms are materialized and developed in this study in Matlab-Fuzzy logic toolbox which has been practically implemented using necessary intelligent control system in electrical engineerin
... Show More This research aims to estimate stock returns, according to the Rough Set Theory approach, test its effectiveness and accuracy in predicting stock returns and their potential in the field of financial markets, and rationalize investor decisions. The research sample is totaling (10) companies traded at Iraq Stock Exchange. The results showed a remarkable Rough Set Theory application in data reduction, contributing to the rationalization of investment decisions. The most prominent conclusions are the capability of rough set theory in dealing with financial data and applying it for forecasting stock returns.The research provides those interested in investing stocks in financial
... Show MoreA Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton
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