An adaptive controller for a class of nonlinear system using direction basis function

Cao, Wenming; Hao, Feng; Zhang, D.M.; Wang, S.J.

doi:10.1109/icosp.2002.1180982

Cited by 8 publications

(1 citation statement)

References 3 publications

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“…Since Wang shoujue proposed Multi Weights Neurons [l,2,3,4,5,6], it have widely applied pattern recognition [7,8,9,10,l 1,12,13,14] > control theory [ 15,16,24] and approximation theory [17] . In my paper, we will apply Multi Weights Neurons approach to determine the delay time for a heating, ventilating and air-conditioning (HVAC) [25,26,27,28] plan to respond to control actions.…”

Section: Introductionmentioning

confidence: 99%

Determining of the Delay Time for a Heating Ventilating and Air-Conditioning Plant Using Multi-Weights Neurons Approach

Hao

Cao

et al.

IFIP — The International Federation for Information Processing

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This paper presents an Multi Weights Neurons approach to determine the delay time for a heating, ventilating and airconditioning (HVAC) plan to respond to control actions. The Multi Weights Neurons is a fully connected four-layer network. An acceleration technique was used to improve the General Delta Rule for the learning process. Experimental data for heating and cooling modes were used with both the Multi Weights Neurons and a traditional mathematical method to determine the delay time. The results show that Multi Weights Neurons can be used effectively determining the delay time for HVAC systems.

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Section: Introductionmentioning

confidence: 99%

Determining of the Delay Time for a Heating Ventilating and Air-Conditioning Plant Using Multi-Weights Neurons Approach

Hao

Cao

et al.

IFIP — The International Federation for Information Processing

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Facial expression recognition based on direction basis function network

Lü

Zhuang

Fang

et al. 2016

2016 Chinese Control and Decision Conference (CCDC)

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Priority ordered direction basis function neural networks and the application for object recognition

Cao¹,

Lü²,

Wang³

2006 IEEE International Conference on Granular Computing

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A brand new architecture of neural networks has been introduced, In this architecture, outputs of direction basis function neurons[1] are with different priorities. It has been discussed that the Priority Ordered Direction Basis Function Neural Network (PODBFNN). The Priority Ordered Direction Basis Function Nets (PODBFN) for object recognition has been analyzed. The experiment shows that the learning speed of the PODBFN are much faster than that of the multilayered feedforward neural networks with existing BP algorithms.

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An adaptive controller for a class of nonlinear system using direction basis function

Cited by 8 publications

References 3 publications

Determining of the Delay Time for a Heating Ventilating and Air-Conditioning Plant Using Multi-Weights Neurons Approach

Determining of the Delay Time for a Heating Ventilating and Air-Conditioning Plant Using Multi-Weights Neurons Approach

Facial expression recognition based on direction basis function network

Priority ordered direction basis function neural networks and the application for object recognition

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