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Hierarchical Stabilization and Tracking Control of a Flexible-Joint Bipedal Robot Based on Anti-Windup and Adaptive Approximation Control
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Bipedal robotic mechanisms are unstable due to the unilateral contact passive joint between the sole and the ground. Hierarchical control layers are crucial for creating walking patterns, stabilizing locomotion, and ensuring correct angular trajectories for bipedal joints due to the system’s various degrees of freedom. This work provides a hierarchical control scheme for a bipedal robot that focuses on balance (stabilization) and low-level tracking control while considering flexible joints. The stabilization control method uses the Newton–Euler formulation to establish a mathematical relationship between the zero-moment point (ZMP) and the center of mass (COM), resulting in highly nonlinear and coupled dynamic equations. Adaptive approximation-based feedback linearization control (so-called adaptive computed torque control) combined with an anti-windup compensator is designed to track the desired COM produced by the high-level command. Along the length of the support sole, the ZMP with physical restrictions serves as the control input signal. The viability of the suggested controller is established using Lyapunov’s theory. The low-level control tracks the intended joint movements for a bipedal mechanism with flexible joints. We use two control strategies: position-based adaptive approximation control and cascaded position-torque adaptive approximation control (cascaded PTAAC). The interesting point is that the cascaded PTAAC can be extended to deal with variable impedance robotic joints by using the required velocity concept, including the desired velocity and terms related to control errors such as position, force, torque, or impedance errors if needed. A 6-link bipedal robot is used in simulation and validation experiments to demonstrate the viability of the suggested control structure.

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Publication Date
Fri Nov 11 2022
Journal Name
International Journal Of Professional Business Review
Measuring the Level of Performance of Accounting Units and Their Impact on the Control Environment
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Purpose: The research aims to study the measurement of the performance of accounting units level of the research sample by using the Federal quality Model European (EFQM)   Design/methodology/approach: the (EFQM) which included seven dimensions "Leadership, Strategic Planning, External Focus, Information and Analysis, Faculty / Staff and Workplace Focus, Process Effectiveness & Outcomes and Achievements" And its effect on the Control Environment, which includes three dimensions: "Integrity, management philosophy and commitment to powers" . the sample is supervisory units of colleges affiliated with the University of Baghdad in Iraq, and a sample was chosen that included fifty-one individuals in the accounting departments.

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Medical Toxicology & Legal Medicine
The relationship between body mass index and asthma control
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Asthma and obesity are both a major public health problems affecting large numbers of individuals across the globe. Link between obesity and asthma is now considered as a recognized fact, and many epidemiological studies, found that overweight and obese people had a higher chance of developing asthma, with more severe symptoms. Assessment of the relationship between body mass index and asthma control. A cross-sectional study, that included 100 patients diagnosed with asthma, attending the respiratory disease consultatory unit at Baghdad teaching hospital. Body mass index was calculated by (BMI= weight in Kg/Height in m2), and Asthma control was assessed using asthma control test questionnaire forma. Statistical analysis done using, Test of

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Publication Date
Thu Oct 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Pressure Control of Electro-Hydraulic Servovalve and Transmission Line Effect
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The effected of the long transmission line (TL) between the actuator and the hydraulic control valve sometimes essentials. The study is concerned with modeling the TL which carries the oil from the electro-hydraulic servovalve to the actuator. The pressure value inside the TL has been controlled by the electro-hydraulic servovalve as a voltage supplied to the servovalve amplifier. The flow rate through the TL has been simulated by using the lumped π element electrical analogy method for laminar flow. The control voltage supplied to servovalve can be achieved by the direct using of the voltage function generator or indirect C++ program connected to the DAP-view program built in the DAP-card data acqu

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Sun Jan 01 2017
Journal Name
Statistical Applications In Genetics And Molecular Biology
Mixture model-based association analysis with case-control data in genome wide association studies
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Abstract<p>Multilocus 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</p> ... Show More
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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning
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This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

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Publication Date
Tue Jun 30 2015
Journal Name
Al-kindy College Medical Journal
Evidence Based Updating of HbA1c Targets: Global Guidelines forGlycemic Control in Type 2 Diabetes Mellitus
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Background:Measurement of hemoglobin A1c (A1C) is a renowned tactic for gauging long-term glycemic control, and exemplifies an outstanding influence to the quality of care in diabetic patients.The concept of targets is open to criticism; they may be unattainable, or limit what could be attained, and in addition they may be economically difficult to attain. However, without some form of targeted control of an asymptomatic condition it becomes difficult to promote care at allObjectives: The present article aims to address the most recent evidence-based global guidelines of A1C targets intended for glycemic control in Type 2 Diabetes Mellitus (T2D).Key messages:Rationale for Treatment Targets of A1C includesevidence for microvascular and ma

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Simulation and Modelling of Electricity Usage Control and Monitoring System using ThingSpeak
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Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

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Publication Date
Sat Nov 05 2016
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Image Compression Based on Cubic Bezier Interpolation, Wavelet Transform, Polynomial Approximation, Quadtree Coding and High Order Shift Encoding
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In this study, an efficient compression system is introduced, it is based on using wavelet transform and two types of 3Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI)) and 1 st order polynomial approximation. Each one is applied on different scales of the image; CBI is applied on the wide area of the image in order to prune the image components that show large scale variation, while the 1 st order polynomial is applied on the small area of residue component (i.e., after subtracting the cubic Bezier from the image) in order to prune the local smoothing components and getting better compression gain. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, t

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Networks And Systems
Using Machine Learning to Control Congestion in SDN: A Review
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