Design of reactive power optimization control for electromechanical system based on fuzzy particle swarm optimization algorithm

Zou, Liren

doi:10.1016/j.micpro.2021.103865

Cited by 23 publications

(7 citation statements)

References 11 publications

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“…Finally, the current adaptive values of all the particles in the population and all past optimal adaptive values are compared to determine the current global optimal value of the population ( ). During the algorithm iteration process, once each particle finds the two aforementioned extreme values 31 – 33 , it updates its speed and position according to the following two Equations: …”

Section: Methodsmentioning

confidence: 99%

Optimization of Burgers creep damage model of frozen silty clay based on fuzzy random particle swarm algorithm

Ya-feng

Cheng

Lin

et al. 2021

Sci Rep

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The creep characteristics of frozen rock and soil are crucial for construction safety in cases of underground freezing. Uniaxial compression tests and uniaxial creep tests were performed at temperatures of − 10, − 15, − 20, and − 25 °C for silty clay used in Nantong metro freezing construction to investigate the effect law of the stress–strain curves and creep curves. However, owing to the complex effects of factors such as temperature and ground pressure, the mechanical properties of underground frozen silty clay are uncertain. The Burgers creep damage model was established by using an elastic damage element to simulate the accelerated creep stage. The traditional particle swarm optimization algorithm was improved using the inertia weight and the fuzzy random coefficient. The creep parameters of the Burgers damage model were optimized using the improved fuzzy random particle swarm algorithm at different temperatures and pressure levels. Engineering examples indicated that the optimized creep model can more effectively characterize the creep stages of frozen silty clay in Nantong metro freezing construction. The improved fuzzy random particle swarm algorithm has wider engineering applicability and faster convergence than the traditional algorithm.

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Section: Methodsmentioning

confidence: 99%

Optimization of Burgers creep damage model of frozen silty clay based on fuzzy random particle swarm algorithm

Ya-feng

Cheng

Lin

et al. 2021

Sci Rep

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“…The particles' dislocation, in two dimensions, is dramatically shown in Fig. 8 [39,40]. The using ANN is a two-layer neural network with a hidden layer in which there are 5 neurons and a sigmoid tangent conversion function in the first and second layers in which the PSO algorithm is investigated and the parameters' influences and interferences are determined.…”

Section: Inertia Weightmentioning

confidence: 99%

Prediction of mechanical properties and hardness of friction stir welding of Al 5083/pure Cu using ANN, ICA and PSO model

et al. 2022

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The effect of parameters involved in prediction of mechanical properties of Friction Stir Welding have been investigated in this study through modeling. For this purpose, the friction stir welding on both sheets of 5083 Aluminum (Al5083) and pure Copper (Cu) was experimentally conducted at first level. Three factors of Rotation Speed (RPM), Traverse Speed (mm/min) and the Tool’s pin angle was examined. During the tentative test, many experiments were not satisfactorily performed. Thanks to a more rigorous study hypothesis, proper samples were obtained by changing the geometry of different tools. In order to overcome the softness of aluminum sheets and the rise of shoulder diameter, and also to avoid the vertical instability of the sheet, shortening the pin’s length was suggested. In this paper, the Full Factorial method has been employed to evaluate the result of Artificial Neural Networks (ANN), Imperialist Competitive Algorithm, Particle Swarm Optimization, and also the effects of input parameters of the process on output parameters. Moreover, Al5083 and Cu joining sheets were analyzed. Micro-hardness and tensile tests have been based on the process’ input parameters to obtain mechanical properties. The function of ANN model demonstrates that it can estimate the number of mechanical properties with an adequate precision. Using the evaluation factors of mechanical properties and micro-hardness and also a R2 ~ 0.943 analysis, the optimum parameters of Al5083 and Cu joining sheets can be anticipated. The rotation speed of 1150 rpm, traverse speed of 40 mm/min, and pin angle of 2° are the optimum conditions based on the average review of analyses. These optimum conditions led to improve the maximum tensile force up to 15 ~ 21%.

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“…Early application research on the monitoring results of a breeding environment focused on the automation and mechanization of equipment, such as heating equipment and rolling shutter systems [5]. Recently, researchers have tried to introduce algorithms or models into environmental monitoring and control processes, such as particle swarm optimization algorithms, fuzzy theory, and fluid mechanics [6][7][8].…”

Section: Application Of Wsn In Breeding Environment Monitoringmentioning

confidence: 99%

Design and Implementation of Intelligent Gateway System for Monitoring Livestock and Poultry Feeding Environment Based on Bluetooth Low Energy

Sun

Zheng

et al. 2021

Information

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This article proposes a gateway system design method applied to the monitoring of a breeding environment based on Bluetooth low energy consumption. Through the queue mechanism and buffer management method, the key information that has the greatest impact on the monitoring effect is sent first, and the feedback mechanism is used to adjust the sampling period of the node in conjunction with the abnormal degree of the monitoring parameter. Experimental results show that the system constructed in this article significantly shortens the transmission delay of key information, with an average packet loss rate of 1.09%. Compared with the traditional method, this method is more timely and effective in handling abnormal data. It effectively solves the short distance and low efficiency of Bluetooth “point-to-multipoint” communication in the case of high data concurrency, and improves the reliability and stability of communication. In turn, the losses caused by environmental mutations are reduced.

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Design of reactive power optimization control for electromechanical system based on fuzzy particle swarm optimization algorithm

Cited by 23 publications

References 11 publications

Optimization of Burgers creep damage model of frozen silty clay based on fuzzy random particle swarm algorithm

Optimization of Burgers creep damage model of frozen silty clay based on fuzzy random particle swarm algorithm

Prediction of mechanical properties and hardness of friction stir welding of Al 5083/pure Cu using ANN, ICA and PSO model

Design and Implementation of Intelligent Gateway System for Monitoring Livestock and Poultry Feeding Environment Based on Bluetooth Low Energy

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