Title :
Approaches to non-linearity compensation of pressure transducer based on HGA-RBFNN
Author :
Wang, Zhiqiang ; Chen, Ping ; Zhao, Mingbo
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Univ. of Technol., Zibo, China
Abstract :
A method is presented to compensate non-linearity of pressure transducer using non-linearity compensation model founded by HGA-RBFNN (hierarchical genetic algorithm RBF neural network). The principle and training method of neural networks are introduced. In this method, the configuration and parameters of non-linearity compensation model are optimized by HGA. The experimental results show that the method has the advantages of high precision and global searching ability. It makes convenient for the pressure transducer to be applied in the measurement.
Keywords :
genetic algorithms; pressure transducers; radial basis function networks; HGA-RBFNN; hierarchical genetic algorithm RBF neural network; nonlinearity compensation model; pressure transducer; Artificial neural networks; Cognition; Computational modeling; Radial basis function networks; Recurrent neural networks; Time series analysis; Transducers; HGA; RBFNN; non-linearity compensation; pressure transducer;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554210
