On the residual based stochastic gradient algorithm for dual-rate sampled-data systems using the polynomial transform technique

Authors:
Yuwu Liao;Dongqing Wang;Xiaoming Chen;Feng Ding
Affiliations:
Department of Physics and Electronics Information Technology, Xiangfan University, Xiangfan, P.R. China;College of Automation Engineering, Qingdao University, Qingdao, P.R. China;Control Science and Engineering Research Center, Jiangnan University, Wuxi, P. R. China;Control Science and Engineering Research Center, Jiangnan University, Wuxi, P. R. China
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

Citing 4
Cited 0

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Combined parameter and output estimation of dual-rate systems using an auxiliary model

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Abstract

This paper uses the polynomial transformation technique to transform an ARX model into a special model that can be identified with dual-rate input-output data, and presents the residual based stochastic gradient algorithm for dual-rate sampled-data systems, and studies convergence properties of the algorithm involved. The analysis indicates that the parameter estimation error consistently converges to zero under some proper conditions. Finally, we test the algorithms proposed in paper by a simulation example and show their effectiveness.