NDLI: Bias compensation recursive algorithm for dual-rate rational models

Content Provider	IET Digital Library
Author	Chen, Jing Liu, Yanjun Zhu, Quanmin
Abstract	In dual-rate rational systems, some output data are missing (unmeasurable) to make the traditional recursive least squares (RLS) parameter estimation algorithms invalid. In order to overcome this difficulty, this study develops a bias compensation RLS algorithm for estimating the missing outputs and then the model parameters. The algorithm based on auxiliary model and particle filter has four steps: (i) to establish an auxiliary model to estimate unmeasurable outputs, (ii) to compensate bias induced by correlated noise, (iii) to add a filter to improve estimation accuracy of the unmeasurable outputs and (iv) to obtain an unbiased parameter estimation. Three examples are selected for simulation demonstrations to give further guarantees on the usefulness of the proposed algorithms. The comparative studies show that the bias compensation RLS is more effective for such systems with dual-rate input and output data.
Starting Page	2184
Ending Page	2193
Page Count	10
ISSN	17518644
Volume Number	12
e-ISSN	17518652
Issue Number	Issue 16, Nov (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/12/16
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2018.5368
Journal	IET Control Theory & Applications
Publisher Date	2018-08-08
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bias Compensation Recursive Algorithm Bias Compensation RLS Algorithm Correlated Noise Dual-rate Rational System Filtering Method in Signal Processing Interpolation And Function Approximation Least Squares Approximation Modelling And Identification Numerical Analysis Particle Filter Recursive Estimation Recursive Least Squares Parameter Estimation Algorithm Signal Processing Theory Simulation Unbiased Parameter Estimation
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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