Research on RBF neural network model reference adaptive control system based on nonlinear U – model-Reference-Cited by-同舟云学术

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Research on RBF neural network model reference adaptive control system based on nonlinear U – model

Published:2019-11-07 Issue:1 Volume:61 Page:46-57
ISSN:0005-1144
Container-title:Automatika
language:en
Short-container-title:Automatika

Author:

Xu Fengxia¹,Wang Shanshan²,Liu Furong³

Affiliation:

1. College of Mechanical and Electrical Engineering, Qiqihar University, Qiqihar, People’s Republic of China

2. College of Computer and Control Engineering, Qiqihar University, Qiqihar, People’s Republic of China

3. State Grid Heilongjiang Electric Power Co., Ltd, Qiqihar, People’s Republic of China

Publisher

Informa UK Limited

Subject

General Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00051144.2019.1668139

Reference11 articles.

1. A pole placement controller for non-linear dynamic plants

2. U-Model-Based Internal Model Control for Non-Linear Dynamic Plants

3. U-Model Based Adaptive Control of Gas Process Plant

4. Direct design of a U-model-based generalized predictive controller for a class of non-linear (polynomial) dynamic plants

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DRNAS: Differentiable RBF neural architecture search method considering computation load in adaptive control;Engineering Applications of Artificial Intelligence;2024-01

2. Design of extended Kalman filtering neural network control system based on particle swarm identification of nonlinear U-model;Automatika;2022-03-18

3. Parallel Solving Method for the Variable Coefficient Nonlinear Equation;International Journal of Circuits, Systems and Signal Processing;2022-01-10

4. Terminal Traction Control of Teleoperation Manipulator With Random Jitter Disturbance Based on Active Disturbance Rejection Sliding Mode Control;IEEE Access;2020

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