An Intelligent Calculation Method of Volterra Time-Domain Kernel Based on Time-Delay Artificial Neural Network

To solve the problems of high complexity and low accuracy in Volterra time-domain kernel calculation of a nonlinear system, this paper proposes an intelligent calculation method of Volterra time-domain kernel by time-delay artificial neural networks (TDANNs) and also designs a root mean square error...

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Bibliographic Details
Published in:Mathematical problems in engineering 2020, Vol.2020 (2020), p.1-11
Main Authors: Zhong, Kaiyang, Chen, Lerui
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Artificial neural networks
Computer simulation
Fault diagnosis
Identification
Kernels
Mathematical models
Neural networks
Neurons
Nonlinear systems
Root-mean-square errors
Time domain analysis
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Summary:To solve the problems of high complexity and low accuracy in Volterra time-domain kernel calculation of a nonlinear system, this paper proposes an intelligent calculation method of Volterra time-domain kernel by time-delay artificial neural networks (TDANNs) and also designs a root mean square error (RMSE) index to choose the neuron number of the network input layer. Firstly, a three-layer TDANN is designed according to the characteristics of the Volterra model. Secondly, the relationship between parameters of TDANN and Volterra time-domain kernel is analyzed, and then three-order expressions of Volterra time-domain kernel are derived. The calculation of Volterra time-domain kernel is completed by network training. Finally, it is verified by a nonlinear system. Simulation results indicate that compared with traditional methods, the new method has higher accuracy, and it can realize the batch calculation of Volterra kernel, which not only improves the calculation efficiency but also provides accurate data for fault diagnosis based on Volterra kernel in further research work.
ISSN:1024-123X
1563-5147
DOI:10.1155/2020/8546963