Two-stage recursive least squares parameter estimation algorithm for output error models
نویسندگان
چکیده
منابع مشابه
Recursive Least Squares Estimation
We start with estimation of a constant based on several noisy measurements. Suppose we have a resistor but do not know its resistance. So we measure it several times using a cheap (and noisy) multimeter. How do we come up with a good estimate of the resistance based on these noisy measurements? More formally, suppose x = (x1, x2, . . . , xn) T is a constant but unknown vector, and y = (y1, y2, ...
متن کاملOn-line Parameter Interval Estimation Using Recursive Least Squares
A bank of recursive least-squares (RLS) estimators is proposed for the estimation of the uncertainty intervals of the parameters of an equation error model (or RLS model) where the equation error is assumed to lie between known upper and lower bounds. It is shown that the off-line least-squares method gives the maximum and minimum parameter values that could have produced the recorded input-out...
متن کاملDecomposition Methods for Least Squares Parameter Estimation
In this paper least squares method with matrix decomposition is revisited and a multiple model formulation is proposed The proposed formulation takes advantage of the well established decomposition methods but possesses a multiple model structure which leads to simpler and more exible implementations and produces more infor mation than the original least squares methods Several application exam...
متن کاملData Filtering Based Recursive and Iterative Least Squares Algorithms for Parameter Estimation of Multi-Input Output Systems
This paper discusses the parameter estimation problems of multi-input output-error autoregressive (OEAR) systems. By combining the auxiliary model identification idea and the data filtering technique, a data filtering based recursive generalized least squares (F-RGLS) identification algorithm and a data filtering based iterative least squares (F-LSI) identification algorithm are derived. Compar...
متن کاملSplitting the recursive least-squares algorithm
Exponentially weighted recursive least-squares (RLS) algorithms are commonly used for fast adaptation. In many cases the input signals are continuous-time. Either a fully analog implementation of the RLS algorithm is applied or the input data are sampled by analog-to-digital (AD) converters to be processed digitally. Although a digital realization is usually the preferred choice, it becomes unf...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical and Computer Modelling
سال: 2012
ISSN: 0895-7177
DOI: 10.1016/j.mcm.2011.09.039