The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated online by a non-linear observer bandwidth, that is as a function of the observation errors. Moreover, with the help of disturbance estimation, a novel sliding manifold is constructed with parameters adaptively adjusted by a dynamic nonlinear bandwidth function to reduce the impact of high gain problems, especially noise-sensitivity. A continuous sliding-mode (CSM) based component is also designed to handle disturbance estimation errors. Third, the stability of the closed loop system, including the proposed controller and estimator, is mathematically proved using the Lyapunov theorem. Finally, the comparative simulation results show that the proposed method has superior robustness and temperature tracking performance.
This research aims to clarify the advantages of using the regression method as analytical procedure in the tax audit to reducing the examination cost , time, effort, human and material resources, and represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side regression method has been applied to the research sample represented by the soft drinks company that is subject to the tax settlement for the year 2014, where the value of sales has been verified by using the regression method without conductinga comprehensive examination. The most important results of the research indicate that the r
... Show MoreIresineherbstii (blood leaves) is a member of the Amaranthaceae family, native to tropical and subtropical areas. It is erect herbaceous, has red and white variety. Different phytochemical constituents were detected as alkaloids, flavonoids, anthocyanins, and others. This herb was used as a pH indicator, insecticide, and dye fabrics. Traditionally it was used for divination purposes and other purposes. Iresinin IV is the major colorant. Different studies were done to evaluate the CNS, immunomodulatory, antibacterial, antiviral, cytotoxic and other effects. Fresh leaves extract was hepatotoxic. This review aimed to demonstrate the morphological features of this herb and to show the clinical studies related to its traditional use.
... Show MoreAccording to different types of democracy Indexes, hybrid regimes or those in the gray zone, make up the majority of regime transformations in the third wave of democracy. However, after nearly three decades, conceptual confusion about hybrid regimes persists and grows, while obstructing the accumulation of knowledge about the nature of hybrid regimes. This leads to significant political repercussions for democratization. This Paper attempts to provide a clearer view of different and overlapping concepts and classifications in this complex field, and sustain development in literature on democratic transformation. To achieve this, we followed an approach based on the classification of concepts and terms in three distinct categories, b
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Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.
The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC
... Show MoreMachine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
... Show MoreEvaluation of the Antibacterial Efficacy of Electrolyzed Oxidizing Water as an Irrigant against Enterococcus faecalis (An In vitro Study), Noor A Khait*, Muna Saleem Kalaf