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Robust State Feedback Control of Electric Heating Furnace Using a New Disturbance Observer
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As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second order system. The SMDO is newly designed to estimate the lumped disturbance, where the estimation error converges to zero asymptotically. The estimation of the disturbances is then used in the control law of the RSFC to reject the system's lumped disturbance. The analytical results demonstrate that the proposed method is asymptotically stable with guaranteeing the tracking error convergence to zero even in the presence of external disturbances. Finally, the comparative simulation study shows the effectiveness of proposed method for the temperature control tracking of the considered furnace application.

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Publication Date
Fri Mar 10 2023
Journal Name
Mathematics
Hamilton–Jacobi Inequality Adaptive Robust Learning Tracking Controller of Wearable Robotic Knee System
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A 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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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
Thermal Buckling of Angle-Ply Laminated Plates Using New Displacement Function
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ABSTRACT

Critical buckling temperature of angle-ply laminated plate is developed using a higher-order displacement field. This displacement field used by Mantari et al based on a constant ‘‘m’’, which is determined to give results closest to the three dimensions elasticity (3-D) theory. Equations of motion based on higher-order theory angle ply plates are derived through Hamilton, s principle, and solved using Navier-type solution to obtain critical buckling temperature for simply supported laminated plates. Changing (α2/ α1) ratios, number of layers, aspect ratios, E1/E2 ratios for thick and thin plates and their effect on thermal

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Determine the best model to predict the consumption of electric energy in the southern region
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Abstract:          

                Interest in the topic of prediction has increased in recent years and appeared modern methods such as Artificial Neural Networks models, if these methods are able to learn and adapt self with any model, and does not require assumptions on the nature of the time series. On the other hand, the methods currently used to predict the classic method such as Box-Jenkins may be difficult to diagnose chain and modeling because they assume strict conditions.

  

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Publication Date
Mon Mar 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Modeling and Simulation of Sensorless Speed Control of a Buck Converter Controlled Dc Motor
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This paper investigate a sensorless speed control of a separately excited dc motor fed from a buck type dc-dc converter. The control system is designed in digital technique by using a two dimension look-up table. The performance of the drive system was evaluated by digital simulation using Simulink toolbox of Matlab.

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of The College Of Languages (jcl)
Dylan Thomas:The Vision of Death as a Prologue to a New Life
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Dylan Thomas (1914-1953) is a modern poet belongs to the apocalyptic movement of the 1940's.This movement is influenced by the doctrines and techniques of surrealism.

              Poetry for him should not be primarily concerned with man in society, but with the celebration of spiritual truth. It should bring to light the hidden causes, hence  his personal interest is to strip darkness and explore the inward motives. To do this he uses a cluster of images: a constant building up and breaking down of images. His poetry depends on the romantic spontaneity, suggestiveness of the Symbolists and the the surrealists' mysterious liberation of the unconsciousness and

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of The College Of Languages
Dylan Thomas:The vision of Death as a Prologue to a New Life
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Dylan Thomas (1914-1953) is a modern poet belongs to the apocalyptic movement of the 1940's.This movement is influenced by the doctrines and techniques of surrealism. Poetry for him should not be primarily concerned with man in society, but with the celebration of spiritual truth. It should bring to light the hidden causes, hence his personal interest is to strip darkness and explore the inward motives. To do this he uses a cluster of images: a constant building up and breaking down of images. His poetry depends on the romantic spontaneity, suggestiveness of the Symbolists and the the surrealists' mysterious liberation of the unconsciousness and the emotional involvement in the dynamics of life. In "Light Breaks

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Publication Date
Wed Aug 25 2021
Journal Name
Caai Transactions On Intelligence Technology
Shoulder girdle recognition using electrophysiological and low frequency anatomical contraction signals for prosthesis control
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Publication Date
Wed Jul 17 2019
Journal Name
Advances In Intelligent Systems And Computing
A New Arabic Dataset for Emotion Recognition
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In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

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