This work is concerned with the vibration attenuation of a smart beam interacting with fluid using proportional-derivative PD control and adaptive approximation compensator AAC. The role of the AAC is to improve the PD performance by compensating for unmodelled dynamics using the concept of function approximation technique FAT. The key idea is to represent the unknown parameters using the weighting coefficient and basis function matrices/vectors. The weighting coefficient vector is updated using Lyapunov theory. This controller is applied to a flexible beam provided with surface bonded piezo-patches while the vibrating beam system is submerged in a fluid. Two main effects are considered: 1) axial stretching of the vibrating beam that leads to the appearance of cubic stiffness term in beam modelling, and 2) fluid effect. Fluid forces are decomposed into two components: hydrodynamic forces due to the beam oscillations and external (disturbance) hydrodynamic loads independent of beam oscillations. Simulation experiments are implemented using MATLAB/SIMULINK to verify the correctness of the proposed controller. Two piezo-patches are bonded on the beam while an impulse force with multi-pulse is applied to excite the beam vibration. The results show the strength of the proposed control structure.
As one type of resistance furnace, the electrical tube furnace (ETF) typically experiences input noise, measurement noise, system uncertainties, unmodeled dynamics and external disturbances, which significantly degrade its temperature control performance. To provide precise, and robust temperature tracking performance for the ETF, a robust composite control (RCC) method is proposed in this paper. The overall RCC method consists of four elements: First, the mathematical model of the ETF system is deduced, then a state feedback control (SFC) is constructed. Third, a novel disturbance observer (DO) is designed to estimate the lumped disturbance with one observer parameter. Moreover, the stability of the closed loop system including controller
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1- The degree of self-control of the educational counselors.
2- The level of work pressures that educational counselors are exposed to from their point of view.
3- The significance of the differences in the degree of self-control and work pressures according to the gender variable (male / female).
4- The relationship between self-control and work stress for the sample as a whole.
The current research was limited to educational counselors of both sexes in Anbar Governorate, Ramadi District, affiliated to the Anbar Education Directorate. The researcher adopted the steps of the relational descriptive approach to achieve the research objectives. The current research community consists of (100) m
... Show MoreThe research aims to contribute to the consolidation of scientific knowledge of compliance control and its role in verifying the proper disposal of funds to manage the wheel of the economy towards achieving targeted development and preserving public money, as well as clarifying the role of tax revenues in strengthening the public treasury and achieving social justice. The analytical descriptive approach was adopted in the process of analyzing The quantitative data collected through personal interviews, and the research reached a set of conclusions, the most important of which is the contribution of compliance control according to its three principles. (Transparency, accountability, and inclusiveness) on the availability
... Show MorePurpose: Determining and identifying the relationships of smart strategic education systems and their potential effects on sustainable success in managing clouding electronic business networks according to green, economic and environmental logic based on vigilance and awareness of the strategic mind.
Design: Designing a hypothetical model that reveals the role and investigating audit and cloud electronic governance according to a philosophy that highlights smart strategic learning processes, identifying its assumptions in cloud spaces, choosing its tools, what it costs to devise expert minds, and strategic intelligence.
Methodology:
Smart cities are using innovative technological solutions to improve the quality of life and service that citizens and visitors receive. Defined as a digital or ecological city, its services depend on information and communication technology infrastructure, such as intelligent automated traffic systems, advanced security management Services, building systems, and the use of automation in offices and homes. The global trend now towards smart cities, sustainable and green cities and other cities, with different nomenclature, the common denominator is the comfort of the individual and the preservation of natural resources. Adopting smart, sustainable, green, or healthy cities is either t
The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
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