A Novel Fuzzy-PSO Controller for Increasing the Lifetime in Power Electronics Stage for Brushless DC Drives

López, Manuel García; Ponce, Pedro; Soriano, Luis Arturo; Molina, Arturo; Rivas, Jaime José Rodríguez

doi:10.1109/access.2019.2909845

Cited by 22 publications

(6 citation statements)

References 31 publications

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“…However, the standard PSO algorithm has the drawbacks of low convergence accuracy and search stagnation. As the number of iterations increases, the diversity of the population decreases, making the algorithm easily fall into the local optimal solution [31]. To overcome the above drawbacks, calculating the iteration success rate of population, we propose an IPSO algorithm with adaptive inertia factor and acceleration factor.…”

Section: E Application Of the Ipso Algorithm To Adaptive Fault-tolerant Sliding Mode Controlmentioning

confidence: 99%

Adaptive Fault-Tolerant Sliding Mode Control for High-Speed Trains With Actuator Faults Under Strong Winds

Zhang

Kong

2020

IEEE Access

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This paper addresses the fault-tolerant control problem for high-speed trains (HSTs) with actuator faults under strong winds. For the healthy system, a non-singular fast terminal sliding mode surface is introduced into the controller, which ensures the system fast converge to the equilibrium point with finite time, and the radial basis function neural network (RBFNN) with the adaptive compensation term of the error is used to approximate the unknown nonlinear disturbances of the train system in strong winds and predict the time delay generated in the train communication network. Through the RBFNN observer established specifically for actuator failures, the real effective factors are identified. Combining with the identified effective factors and predicted time delay, an adaptive fault-tolerant sliding mode control method is established for train systems. With dynamic parameters and position update strategy guided by negative gradient thought, an improved particle swarm optimization algorithm is proposed to optimize the uncertain parameters of control method, which weakens the chattering phenomenon from the sliding mode controller and improves the control accuracy. Simulation results show that the proposed method has better tracking performance and real-time performance compared with other fault-tolerant control methods under various operating conditions, which ensures the running safety of HSTs under different strong winds.

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Section: E Application Of the Ipso Algorithm To Adaptive Fault-tolerant Sliding Mode Controlmentioning

confidence: 99%

Adaptive Fault-Tolerant Sliding Mode Control for High-Speed Trains With Actuator Faults Under Strong Winds

Zhang

Kong

2020

IEEE Access

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“…Another constraint is the inverter output voltage. The H-bridge inverter PWM chopping output is limited by the DC voltage, expressed in (6).…”

Section: B Optimization Problem Formation and Solutionmentioning

confidence: 99%

Data-Driven Digital Direct Position Servo Control by Neural Network With Implicit Optimal Control Law Learned From Discrete Optimal Position Tracking Data

et al. 2019

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To get better control performance in motor control, more and more researches tend to apply non-linear control laws in the field of motor control. However, most conventional non-linear control theory is based on explicit model of controlled object and often resulting in complexity. Besides, the control parameters tuning is mainly aiming at stability of the system. No valid direct performance-oriented nonlinear control theory has been proposed. Facing the limitations, this paper presents a direct motor position control in an implicit data-driven manner. Unlike conventional non-linear motor controls that are based on explicit models and with stability-based parameters tuning, this study gives performance-oriented non-linear control by mastering non-linear discrete optimal control law in an implicit data-learning manner. Firstly, optimal data of position tracking problem is obtained by solving optimization problem. Secondly, the implicit discrete optimal control law hidden in data is learned by a BP neural network. Finally, the learned control law is implemented in real-time control to reproduce optimal control performance. Simulation and experiment results validated the feasibility of the data-driven controller, which could be helpful for performance-oriented non-linear control designs. The merits and further improvements are also discussed.INDEX TERMS Position control, implicit discrete optimal control, artificial neural network, motor, data learning.

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“…Diante dos desafios apresentados no que se refere à inserção de motores elétricos na indústria, este trabalho propõe a análise de dois controladores, um controlador PID discreto e um controlador Fuzzy-PID aplicados à uma ventoinha. De forma geral, os controladores Fuzzy-PID têm sido utilizados em diversas aplicações em várias áreas da engenharia, como por exemplo em controle de motores do tipo BLDC (motor sem escovas de corrente continua do inglês brushless direct current) para o aumento de vida útil [1], em processos químicos de um sistema de biomassa para uma caldeira a vapor [2] e em outras aplicações complexas com funções de transferência de ordem superior não lineares. O controlador Fuzzy-PID integra a vantagem de ambas as estruturas de controle e, como consequência uma melhoria no desempenho tanto em termos do transitório quanto ao estacionário [3].…”

Section: Introductionunclassified

Desenvolvimento de um controlador Fuzzy-PID aplicado à uma ventoinha

Ribeiro¹,

Silva²,

Siqueira³

et al. 2021

Anais Do 15. Congresso Brasileiro De Inteligência Computacional

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Plantas que operam em malha aberta, ou seja, sem sensoriamento e controle, tendem a ser muito sensíveis a perturbações, além de normalmente não apresentarem desempenho transitório adequado em diversas implementações. Assim sendo, este trabalho apresenta os resultados de um estudo de caso sobre a aplicação de estratégias de controle PID e controle híbrido FUZZY-PID aplicados à uma ventoinha de computador. O presente trabalho fornece uma análise sobre o comportamento, parametrização, e principais diferenças apresentadas no comportamento dessa planta. A partir dos resultados, nota-se que com um controle adaptativo bem sintonizado é possível obter melhores parâmetros de desempenho, entretanto o desenvolvimento de um projeto como este nem sempre é a melhor solução custo-benefício, em função de sua complexidade de desenvolvimento.

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A Novel Fuzzy-PSO Controller for Increasing the Lifetime in Power Electronics Stage for Brushless DC Drives

Cited by 22 publications

References 31 publications

Adaptive Fault-Tolerant Sliding Mode Control for High-Speed Trains With Actuator Faults Under Strong Winds

Adaptive Fault-Tolerant Sliding Mode Control for High-Speed Trains With Actuator Faults Under Strong Winds

Data-Driven Digital Direct Position Servo Control by Neural Network With Implicit Optimal Control Law Learned From Discrete Optimal Position Tracking Data

Desenvolvimento de um controlador Fuzzy-PID aplicado à uma ventoinha

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