Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

Moaveni, Bijan; Fathabadi, Fatemeh Rashidi; Molavi, Ali

doi:10.1002/asjc.2472

Cited by 28 publications

(17 citation statements)

References 44 publications

(71 reference statements)

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“…Here, the two systems are briefly analyzed first. Fuzzy control [8,9] includes access terminals, monitoring equipment, access and output ports, mechanisms, controlled objects, and inspection systems. The basic principle of fuzzy control is shown in Figure 4.…”

Section: Application Of Ai In Electrical Automationmentioning

confidence: 99%

Application and Thinking of Artificial Intelligence in Electrical Automation

Chen

2022

Wireless Communications and Mobile Computing

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With the vigorous development of China’s market economy, a new generation of artificial intelligence technology has also developed rapidly, which has strongly promoted the optimization and improvement of China’s electrical automation control system. The use of artificial intelligence technology in power automation systems mainly has the following two advantages: it can reduce the manufacturing time of power products, thereby increasing the number of workers manufacturing power products and promoting enterprises to conduct larger-scale machine manufacturing, thereby improving the comprehensive economic benefits of enterprise machine manufacturing, but also improve the quality of manufactured products of electric power products. Since the machine control of artificial intelligence is more efficient than manual manufacturing, it reduces the manufacturing problems caused by the subjective factors of manufacturing workers to a certain extent and thus improves the qualification rate of machine production. Electrical engineering plays an important role in China’s urban development, and automatic control is an important part of electrical engineering, which can have a direct impact on the quality of electrical engineering. Therefore, in order to promote the healthy development of cities in China, this paper studies the application of artificial intelligence technology in electrical engineering automation by analyzing relevant data, in order to provide a reliable basis for relevant personnel to carry out their work.

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Section: Application Of Ai In Electrical Automationmentioning

confidence: 99%

Application and Thinking of Artificial Intelligence in Electrical Automation

Chen

2022

Wireless Communications and Mobile Computing

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“…As shown in Figure 5, to match the load with the solar array, in order to absorb the maximum power, the buck converter is used as a power processor [10]. [12]- [13]. To design a fuzzy controller and to select fuzzy rules, there should be a complete understanding of the photovoltaic system's behavior.…”

Section: Dc-dc Buck Convertermentioning

confidence: 99%

Designing an Intelligent Maximum Power Point Tracking (MPPT) for a Rooftop Solar Array

Balali¹

2021

IJMTST

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By considering the limitation of the size of houses, the permanent inaccessibility of the solar radiation energy, and also the low efficiency of solar cells, a PV system requires the maximum power point tracking(MPPT). The main issue with using solar cells is to reach its maximum power, which is intensified by change in the temperature and radiation. In this paper, among MPPT methods, the Perturb and Observe (P&O) method, has been designed which has high reliability and traceability. However, due to the output power oscillation around the operating point in P&O method, an optimization fuzzy/bee algorithm is used for maximum power point tracking so that without the need for temperature and light sensors, reduction of output power oscillations can be achieved. Simulation results indicate that by using the fuzzy/ bee method, in addition to reducing the fluctuation around the operating point, the speed of reaching to the optimal point is maximized.

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“…In this study, the dehydration of a PEMFC was analysed through classification based on the knowledge from an operator over a FC. Results revealed that suitable nonlinearities like electrical features and uncertainties can be mirrored with linguistic rules, an essential feature of this tool [19]. However, one of the main disadvantages of fuzzy logic strategies is the computational requirement when features are increased and thus, rules are expanded [20].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Approach for Modeling and Control of a Commercial Heliocentris FC50 PEM Fuel Cell System

2021

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In recent years, machine learning (ML) has received growing attention and it has been used in a wide range of applications. However, the ML application in renewable energies systems such as fuel cells is still limited. In this paper, a prognostic framework based on artificial neural network (ANN) is designed to predict the performance of proton exchange membrane (PEM) fuel cell system, aiming to investigate the effect of temperature and humidity on the stack characteristics and on tracking control improvements. A large part of the experimental database for various operating conditions has been used in the training operation to achieve an accurate model. Extensive tests with various ANN parameters such as number of neurons, number of hidden layers, selection of training dataset, etc., are performed to obtain the best fit in terms of prediction accuracy. The effect of temperature and humidity based on the predicted model are investigated and compared to the ones obtained from real-time experiments. The control design based on the predicted model is performed to keep the stack operating point at an adequate power stage with high-performance tracking. Experimental results have demonstrated the effectiveness of the proposed model for performance improvements of PEM fuel cell system.

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Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

Cited by 28 publications

References 44 publications

Application and Thinking of Artificial Intelligence in Electrical Automation

Application and Thinking of Artificial Intelligence in Electrical Automation

Designing an Intelligent Maximum Power Point Tracking (MPPT) for a Rooftop Solar Array

Machine Learning Approach for Modeling and Control of a Commercial Heliocentris FC50 PEM Fuel Cell System

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