Journal
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 23, Issue 5, Pages 1952-1960Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2014.2387216
Keywords
Dual-rate; Hammerstein systems; hierarchical identification principle; key term separation principle; least squares; parameter estimation
Funding
- National Natural Science Foundation of China [61472195]
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This brief concerns parameter identification for a dual-rate Hammerstein CARMA system. By combining the polynomial transformation technique and the hierarchical identification principle, this brief transforms a dual-rate nonlinear Hammerstein CARMA system into a bilinear dual-rate identification model, and presents a hierarchical least squares algorithm to estimate the parameter vectors of the bilinear dual-rate identification model. Moreover, by using the key term separation principle, this brief transforms the dual-rate nonlinear Hammerstein CARMA system into a linear dual-rate identification model, and presents a key term separation based least squares algorithm to estimate the parameter vector of the linear dual-rate identification model. The two proposed methods possess higher computational efficiency compared with the previous over-parameterization least squares method in which many redundant parameters need estimating. The simulation results show the effectiveness of the two proposed algorithms.
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