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A new two-axis solar tracker based on the online optimization method:Experimental investigation and neural network modeling

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Energy and AI 2023年第4期14卷 341-359页

作者： Amir Pouya Masoumi Vahid Bagherian ali reza tavakolpour-saleh Elham Masoomi Department of Mechanical and Aerospace Engineering Shiraz University of TechnologyShirazIran Department of Mechanical Engineering Shiraz UniversityShirazIran Department of Computer Engineering Qazvin BranchIslamic Azad UniversityQazvinIran

This article presents a new two-axis solar tracker based on an online optimization algorithm so as to track the position of the sun without using its movement *** this research,four well-known optimization algorithms are employed to find the two unknown parameters named azimuth and zenith angles,which determine the position of the *** magnitude of the sunray is considered as the cost function of all ***,several experiments are carried out to find the best optimization algorithm with optimal population size,number of iterations,and also the best initialization *** initialization leads to faster convergence compared to random *** results clearly show that the particle swarm optimization algorithm with a population size of 15 and 7 iterations using uniform initialization method has better performance than the other algorithms,with a convergence time of less than 40 *** average fitness value or voltage received by the tracker is 2.4 Volts in this method,which is higher than other *** also performs well with a population size of 15 and 7 ***,the artificial neural network with one hidden layer and 20 neurons is employed to predict these two parameters in each day and moment in a year in Shiraz city according to the experimental data extracted from *** of the day from January and the time are inputs and zenith and azimuth angles are considered the output of neural network *** performance of the proposed ANN model is evaluated using regression plots,demonstrating a strong correlation between predicted and target ***,the outcomes reveal the feasibility of using online optimization algorithms and neural network modeling in an effort to bypass the complex mathematical model of mechatronic systems and predict the movement of the sun automatically.

关键词： Intelligent two-axis solar tracker Optimization algorithm Particle swarm optimization algorithm Online optimization method Artificial neural network

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Robust control approach for handling matched and/or unmatched uncertainties in port-controlled Hamiltonian systems

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IET Cyber-Systems and Robotics 2019年第3期1卷 73-80页

作者： Tahereh Binazadeh Mahsa Karimi ali reza tavakolpour-saleh Department of Electrical and Electronic Engineering Shiraz University of TechnologyShirazIran Department of Mechanical and Aerospace Engineering Shiraz University of TechnologyShirazIran

This study considers the problem of robust interconnection and damping assignment passivity-based control approach(IDA-PBC)for underactuated mechanical systems from two points of ***,the robustness of IDA-PBC in the presence of non-vanishing matched and unmatched uncertainties is analysed and sufficient conditions are derived to ensure ultimate boundedness of ***,the robust control design is provided by adding a new control input to the former controller designed by IDA-PBC,such that asymptotic stability of the closed-loop system in the face of non-vanishing matched uncertainties is ***,the proposed robust controller is evaluated through simulations of two practical examples,*** inertia wheel pendulum and a single-link elastic joint *** simulation outcomes clearly reveal the effectiveness of the presented robust controller.

关键词： matched vanishing Hamiltonian

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