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Integral Sliding Mode Control Design for Electronic Throttle Valve System
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Abstract

 One of the major components in an automobile engine is the throttle valve part. It is used to keep up with emissions and fuel efficiency low. Design a control system to the throttle valve is newly common requirement trend in automotive technology. The non-smoothness nonlinearity in throttle valve model are due to the friction model and the nonlinear spring, the uncertainty in system parameters and non-satisfying the matching condition are the main obstacles when designing a throttle plate controller.

In this work, the theory of the Integral Sliding Mode Control (ISMC) is utilized to design a robust controller for the Electronic Throttle Valve (ETV) system. From the first instant, the electronic throttle valve dynamics is represented by the nominal system model, this model is not affected by system parameters uncertainty and the non-smooth nonlinearities. This is a consequence of applying the integral sliding mode control. The ISMC consists of two part; the first is the nominal control which is used to control the nominal system, while the second is a discontinuous part which is used to eliminate the effects of the parameters uncertainty and the non-smooth nonlinearities from system model. These features for the ISMC are proved mathematically and demonstrated numerically via seven numerical simulations and for different desired trajectories.  The simulation results clarify that for different system parameters, the ETV behaves as a nominal system. This enables to freely and precisely select the system response characteristics and the time required for the throttle angle to reach the desired value. Moreover the ability to deal with the chattering problem is demonstrated through the worked  simulation tests, where the chattering is eliminated via approximating the signum function by arc tan function.

 Keywords: Electronic throttle valve, Nonlinear spring model, Integral sliding mode control, Non-smooth model.

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Publication Date
Thu Aug 08 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Novel Technique for Alveolar Ridge Expansion: A Comparative Clinical Study
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Background: Piezosurgery improved the split approach by making it safer, easier, and less prone to complications when treating extremely atrophic crests. Densah drills, with their unique design, expand the ridge by densifying bone in a reverse, non-cutting mode. Objective: To assess the effectiveness of sagittal piezosurgery, which involves cutting bone to the full implant depth and then expanding it using osseodensification drills. We use this technique to expand narrow alveolar bones and simultaneously place dental implants in the maxillary and mandibular arches. Methods: Fourteen patients received 31 dental implants. The maxillary arch received 19, and the mandible received 12 dental implants. This study will include patients who

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
Thermal Performance Analysis of Compact Heat Exchangers for Thermoelectric Generators
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The efficiency of internal combustion engines (ICE) is usually about thirty percent of the total energy of the fuel. The residual energy is lost in the exhaust gas, the lubrication, and the cooling water in the radiators. Recently much of the researcher’s efforts have focused on taking advantage of wasted energy of the exhaust gas. Using a thermoelectric generator (TEG) is one of the promising ways. However, TEG depends entirely on the temperature difference, which may be offered by the exhaust muffler. An experimental test has been conducted to study the thermal performance of a different muffler internal design. The researchers resort to the use of lost energy in an ICE using TEG, which is one of the ways to take adv

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Publication Date
Mon Mar 30 2026
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Adaptive Security Model for Data Protection Using Behavioral User Authentication
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Credential compromise is one of the most widespread security threats, allowing adversaries to bypass traditional authentication measures and impersonate legitimate users. Traditional intrusion detection systems are often based on network-level or macro-behavioral indicators, which can be easily spoofed by an attacker, thus compromising the effectiveness of those mechanisms. This study presents an improved adaptive intrusion detection system to authenticate user behavior based on micro-digital behavioral profiling. It involves the use of timing of keystrokes, micro-mouse, navigation in the application, and interaction rhythm signatures. The proposed system uses a hybrid model consisting of Long Short-Term Memory (LSTM) sequence predi

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Publication Date
Thu Apr 21 2022
Journal Name
Journal Of Petroleum Research And Studies
Smart Well Modelling for As Reservoir in AG Oil Field
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Intelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we

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Publication Date
Sat Jan 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems Using Convolutional Neural Network
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AA Abbass, HL Hussein, WA Shukur, J Kaabi, R Tornai, Webology, 2022 Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The mai

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Publication Date
Sat Jan 05 2019
Journal Name
Iraqi Journal Of Physics
Fabrication and characterization of porous silicon for humidity sensor application
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Porous Silicon (PS) layer has been prepared from p-type silicon by electrochemical etching method. The morphology properties of PS samples that prepared with different current density has been study using atom force measurement (AFM) and it show that the Layer of pore has sponge like stricture and the average pore diameter of PS layer increase with etching current density increase .The x-ray diffraction (XRD) pattern indicated the nanocrystaline of the sample. Reflectivity of the sample surface is decrease when etching current density increases because of porosity increase on surface of sample. The photolumenses (PL) intensity increase with increase etching current density. The PL is affected by relative humidity (RH) level so we can use

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Publication Date
Thu Sep 15 2022
Journal Name
Knowledge And Information Systems
Multiresolution hierarchical support vector machine for classification of large datasets
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Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
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In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

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Publication Date
Sun Jun 01 2014
Journal Name
2014 International Conference On Computer And Information Sciences (iccoins)
Proposed conceptual model for E-service quality in Malaysian universities
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Publication Date
Sun May 16 2021
Journal Name
Graphs And Combinatorics
Commuting Involution Graphs for Certain Exceptional Groups of Lie Type
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Abstract<p>Suppose that <italic>G</italic> is a finite group and <italic>X</italic> is a <italic>G</italic>-conjugacy classes of involutions. The commuting involution graph <inline-formula><alternatives><tex-math>$${\mathcal {C}}(G,X)$$</tex-math><math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mrow> <mi>C</mi> <mo>(</mo> <mi>G</mi> <mo>,</mo> <mi>X</mi> <mo>)</mo> </mrow> </math></alternatives></inline-formula> is</p> ... Show More
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