Continuous-time subspace system identification using generalized orthonormal basis functions
نویسندگان
چکیده
This paper proposes a new subspace identification algorithm for continuous-time systems using generalized orthonormal basis functions. It is shown that a generalized orthonormal basis induces the transformation of continuoustime stochastic systems into discrete-time stochastic systems, and that the transformed noises have the ergodicity properties. With these basic observations, the standard subspace identification methods such as the MOESP algorithm are applied to estimate the system matrices.
منابع مشابه
Filters Parametrized by Orthonormal Basis Functions for Active Noise Control
Parametrization of filters on the basis of orthonormal basis functions have been widely used in system identification and adaptive signal processing. The main advantage of using orthonormal basis functions for a filter parametrization lies in the possibility of incorporating prior knowledge of the system dynamics into the identification process and adaptive signal process. As a result, a more a...
متن کاملContinuous-time subspace identification in closed-loop
This paper deals with the problem of continuoustime model identification and presents a subspace-based algorithm capable of dealing with data generated by systems operating in closed-loop. The algorithm is developed by reformulating the identification problem from the continuous-time model to an equivalent one to which discrete-time subspace identification techniques can be applied. More precis...
متن کاملConstructing Two-Dimensional Multi-Wavelet for Solving Two-Dimensional Fredholm Integral Equations
In this paper, a two-dimensional multi-wavelet is constructed in terms of Chebyshev polynomials. The constructed multi-wavelet is an orthonormal basis for space. By discretizing two-dimensional Fredholm integral equation reduce to a algebraic system. The obtained system is solved by the Galerkin method in the subspace of by using two-dimensional multi-wavelet bases. Because the bases of subs...
متن کاملNew Modelling and Robust Identification of MIMO linear systems on the generalized Orthonormal bases with ordinary poles
In this paper we propose a new modeling technique for LTI multivariable systems using the generalized Orthonormal basis functions with ordinary poles. Once the model structure is built we proceed to update the membership set of the resulting model parameters through the execution of unknown but bounded error identification algorithms. This updating aims to synthesize a robust control strategy. ...
متن کاملOrthonormal Basis Functions for Continuous-Time Systems and Lp Convergence
In this paper, model sets for continuous–time linear time invariant systems that are spanned by fixed pole orthonormal bases are investigated. These bases generalise the well known Laguerre and two–parameter Kautz cases. It is shown that the obtained model sets are norm dense in the Hardy space H1(Π) under the same condition as previously derived by the authors for the norm denseness in the (Π ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2004