Results 231 to 240 of about 1,355,935 (279)

Adaptive sliding mode control of maglev system based on RBF neural network minimum parameter learning method

Measurement, 2019
The electromagnet levitation control system is the core component of maglev trains, which has a significant influence on the performance of the maglev train.
Yougang Sun, Junqi Xu, H. Qiang, Chen Chen, G. Lin   +4 more
semanticscholar   +1 more source

A RBF neural networks based feature

2010 8th World Congress on Intelligent Control and Automation, 2010
A RBF (Back-Propogation) neural networks based feature is applied to the target recognition, which aims at only recognition of the target feature and searches the hyperplane of the local space taking the target feature as center. The classifier integrates the target feature with RBF ANNs.
Lianglong Da, Guangzhi Shi, Junchuan Hu, Yuyang Li   +3 more
openaire   +1 more source

Ml-rbf: RBF Neural Networks for Multi-Label Learning

Neural Processing Letters, 2009
Multi-label learning deals with the problem where each instance is associated with multiple labels simultaneously. The task of this learning paradigm is to predict the label set for each unseen instance, through analyzing training instances with known label sets.
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L p approximation capability of RBF neural networks

Acta Mathematica Sinica, English Series, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nan, Dong, Wu, Wei, Long, Jin Ling, Ma, Yu Mei, Sun, Lin Jun   +4 more
openaire   +1 more source

Self-Organizing RBF Neural Network Using an Adaptive Gradient Multiobjective Particle Swarm Optimization

IEEE Transactions on Cybernetics, 2019
One of the major obstacles in using radial basis function (RBF) neural networks is the convergence toward local minima instead of the global minima. For this reason, an adaptive gradient multiobjective particle swarm optimization (AGMOPSO) algorithm is ...
Hong-gui Han, Xiaolong Wu, Lu Zhang, Yu Tian, J. Qiao   +4 more
semanticscholar   +1 more source

Observer-Based Adaptive Sliding Mode Control of NPC Converters: An RBF Neural Network Approach

IEEE transactions on power electronics, 2019
This paper proposes a novel control strategy for three-level neutral-point-clamped (NPC) power converter. The proposed control scheme consists of three control loops, i.e., instantaneous power tracking control loop, voltage regulation loop, and voltage ...
Yunfei Yin, Jianxing Liu, J. Sanchez, Ligang Wu, S. Vazquez, J. I. Leon, L. Franquelo   +6 more
semanticscholar   +1 more source

Adaptive RBF Neural Network Control

2012
Since the idea of the computational abilities of networks composed of simple models of neurons was introduced in the 1940s [1], neural network techniques have undergone great developments and have been successfully applied in many fields such as learning, pattern recognition, signal processing, modeling, and system control.
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Harmonic identification based on RBF neural network

2016 35th Chinese Control Conference (CCC), 2016
As one of the important equipment for vibration test, hydraulic shaking table can produce great vibration force and displacement of vibration, , widely applied in engineering field. In the test system of hydraulic shaking table, because of the existence of non-linearities, there exists higher harmonic in system response signal when the shaking table is
Jianjun Yao, Shuo Chen, Qingtao Niu, Le Zhang, Cheng Sun, Zhenshuai Wan   +5 more
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Corrective action planning using RBF neural network

Applied Soft Computing, 2007
In recent years, voltage limit violation and power system load-generation imbalance, i.e., line loading limit violation have been responsible for several incidents of major network collapses leading to partial or even complete blackouts. Alleviation of line overloads is the suitable corrective action in this regard.
Daya Ram, Laxmi Srivastava, Manjaree Pandit, Jaydev Sharma   +3 more
openaire   +1 more source

Digital RBF Neural Network Control

2012
This chapter introduces adaptive Runge–Kutta–Merson method for digital RBF neural network controller design. Two examples for mechanical controls are given, including digital adaptive control for a servo system and digital adaptive control for two-link manipulators.
openaire   +1 more source