Fuzzy Neural Network PID Control Based on RBF Neural Network for Variable Configuration Spacecraft

Wang, Ran; Zhou, Zhicheng; Guang-ji, QU

doi:10.1109/iaeac.2018.8577860

Cited by 19 publications

(2 citation statements)

References 2 publications

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“…Due to the possession of non-linearity, and the ability of online learning (transferring the real-time experience to AI models), the AI-aided PI/PR online control methods have been widely used in different areas, such as dc-dc converter [32], [3], [33], [34], spacecraft [35], exoskeleton systems [36], and electric vehicle charging system [37]. However, there are generally two groups of approaches utilized to do that, design and control, as discussed below.…”

Section: Ai Applications In Linear Controllers Of Power Convertersmentioning

confidence: 99%

Artificial Intelligence Techniques for Enhancing the Performance of Controllers in Power Converter-Based Systems—An Overview

Gao,

Wang,

Dragicevic

et al. 2023

IEEE Open J. Ind. Applicat.

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The integration of artificial intelligence (AI) techniques in power converter-based systems has the potential to revolutionize the way these systems are optimized and controlled. With the rapid advancements in AI and machine learning technologies, this paper presents the analysis and evaluation of these powerful tools as well as in computational capabilities of microprocessors that control the converter. This paper provides an overview of AI-based controllers, with a focus on online/offline supervised, unsupervised, and reinforcement-trained controllers. These controllers can be used to create surrogates for inner control loops, complete power converter controllers, and external supervisory or energy management control. The benefits of using AI-based controllers are discussed. AI-based controllers reduce the need for complex mathematical modeling and enable near-optimal real-time operation via computational efficiency. This can lead to increased efficiency, reliability, and scalability of power converter-based systems. By using physics-informed methods, a deeper understanding of the underlying physical processes in power converters can be achieved and the control performance can be made more robust. Finally, by using datadriven methods, the vast amounts of data generated by power converter-based systems can be leveraged to analyze the behavior of the surrounding system and thereby forming the basis for adaptive control. This paper discusses several other potential disruptive impacts that AI could have on a wide variety of power converter-based systems.

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Section: Ai Applications In Linear Controllers Of Power Convertersmentioning

confidence: 99%

Artificial Intelligence Techniques for Enhancing the Performance of Controllers in Power Converter-Based Systems—An Overview

Gao,

Wang,

Dragicevic

et al. 2023

IEEE Open J. Ind. Applicat.

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“…Aplicações de Redes Neurais Artificiais (RNA), Algoritmos Genéticos e Lógica Fuzzy, tem sido utilizadas para métodos de sintonia dos controladores PID de forma adaptativa [5], [6], [7]. Em [8], é abordado um controlador PID adaptativo via redes Neurais para controle atitude de quadricopteros.…”

Section: Introductionunclassified

Controlador PID Adaptativo Via Redes Neurais-LMS Para Controle de Altitude de Quadricoptero

Abreu¹,

Neto²

2020

Anais Do 14. Congresso Brasileiro De Inteligência Computacional

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Resumo -O desenvolvimento de uma metodologia para sintonia online de controladores PID adaptativo via Redes Neurais Artificiais baseado no algoritmo de treinamento LMS é abordada neste artigo. Sistemas físicos sujeitos a variações paramétricas e distúrbios externos requerem um controlador com auto ajuste em seus ganhos. O algoritmo proposto ajusta continuamente os parâmetros do controlador PID de forma adaptativa. A metodologia é aplicada a um controle de altitude de um veiculo aéreo não tripulado (VANT) do tipo quadricoptero. Este veículo é uma aeronave do tipo multirotor e apresenta quatro motores que são responsáveis por sua movimentação e possui a capacidade de decolagem e pousos verticais. Resultados experimentais confirmam o bom desempenho do método, seguindo uma trajetória de referência mesmo na presença de variações paramétricas na planta.

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Combination of Parallel and Cascade Control on the Example of Two Rotor Aerodynamical System with the Use of FOPID and PID Controllers

Żegleń-Włodarczyk

2023

Lecture Notes in Networks and Systems

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Fuzzy Neural Network PID Control Based on RBF Neural Network for Variable Configuration Spacecraft

Cited by 19 publications

References 2 publications

Artificial Intelligence Techniques for Enhancing the Performance of Controllers in Power Converter-Based Systems—An Overview

Artificial Intelligence Techniques for Enhancing the Performance of Controllers in Power Converter-Based Systems—An Overview

Controlador PID Adaptativo Via Redes Neurais-LMS Para Controle de Altitude de Quadricoptero

Combination of Parallel and Cascade Control on the Example of Two Rotor Aerodynamical System with the Use of FOPID and PID Controllers

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