Command Filter-Based Adaptive Fuzzy Finite-Time Output Feedback Control of Nonlinear Electrohydraulic Servo System

IEEE Transactions on Instrumentation and Measurement, Journal Year: 2022, Volume and Issue: 71, P. 1 - 10

Published: Jan. 1, 2022

In this paper, the command filter-based adaptive fuzzy finite-time output feedback control (FOFC) is investigated for Electro-hydraulic servo system. For uncertainties in system, we utilize logic systems (FLSs) to estimate these uncertain nonlinearities and state observer established approximate unmeasurable hydraulic cylinder stem speed internal force. Then, a finite time proposed achieve high tracking precision, where errors can be regulated into small neighborhood around equilibrium proved by Lyapunov stability theory. Moreover, filter introduced avoid explosion of complexity backstepping procedure, compensation mechanism developed compensate errors. Finally, simulation results are provided demonstrate effectiveness control.

Language: Английский

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Recurrent context layered radial basis function neural network for the identification of nonlinear dynamical systems

Neurocomputing, Journal Year: 2024, Volume and Issue: 580, P. 127524 - 127524

Published: March 5, 2024

Language: Английский

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Distributed adaptive fixed-time formation control for UAV-USV heterogeneous multi-agent systems

Ocean Engineering, Journal Year: 2022, Volume and Issue: 267, P. 113240 - 113240

Published: Dec. 5, 2022

Language: Английский

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Recent advances and prospects in hypersonic inlet design and intelligent optimization

Aerospace Science and Technology, Journal Year: 2024, Volume and Issue: 146, P. 108953 - 108953

Published: Feb. 2, 2024

Language: Английский

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Application of artificial intelligence technologies and big data computing for nuclear power plants control: a review

Frontiers in Nuclear Engineering, Journal Year: 2024, Volume and Issue: 3

Published: Feb. 23, 2024

Nuclear power plants produce a massive amount of clean energy and necessitate safe operation through intelligence technologies. Recently, the rapid advancements in communication infrastructures including artificial intelligence, big data computing, Internet Things devices moving nuclear industries towards digitalization to improve safety. The integration these technologies into sector offers effective tactics addressing several challenges control plants. This can be achieved insights generated from amounts data. paper comprehensively reviews literature on data, seeking provide holistic perspective their relations how they integrated with utilization computing platforms boosts deployment analytics effectively Further, this review also points out future opportunities as well for applying industry.

Language: Английский

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Evolving temporal convolutional neural networks for modeling turntable servo systems

Applied Soft Computing, Journal Year: 2025, Volume and Issue: unknown, P. 112800 - 112800

Published: Jan. 1, 2025

Language: Английский

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Intelligent prediction for digging load of hydraulic excavators based on RBF neural network

Measurement, Journal Year: 2022, Volume and Issue: 206, P. 112210 - 112210

Published: Nov. 21, 2022

Language: Английский

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A model-free terminal sliding mode control for robots: Achieving fixed-time prescribed performance and convergence

ISA Transactions, Journal Year: 2023, Volume and Issue: 144, P. 330 - 341

Published: Nov. 9, 2023

Language: Английский

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Fault tolerant control of nonlinear hydraulic systems with prescribed performance constraint

ISA Transactions, Journal Year: 2022, Volume and Issue: 131, P. 1 - 14

Published: May 10, 2022

Language: Английский

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Adaptive super-twisting fast nonsingular terminal sliding mode control with ESO for high-pressure electro-pneumatic servo valve

Control Engineering Practice, Journal Year: 2023, Volume and Issue: 134, P. 105483 - 105483

Published: March 9, 2023

Language: Английский

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