Journal ArticleDOI
Identification of lumped systems Identification of lumped linear time-varying parameter systems via Poisson moment functionals
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TLDR
In this article, the effect of unknown initial conditions of the process is included in the related operational matrices thereby making the algorithm useful in the important practical situation wherein process data is available over an arbitrary but active length of time.Abstract:
Poisson Moment Functionals (PMF) of input and ouput of a Single-Input-Single-Output (SISO) system characterized by a linear differential equation with time varying coefficients, are used in a general algorithm of parameter identification. The method is a generalized version of certain recent algorithms proposed by Saba and Prasada Rao (1979) for fixed parameter systems. The effect of unknown initial conditions of the process is included in the related operational matrices thereby making the algorithm useful in the important practical situation wherein process data is available over an arbitrary but active length of time.read more
Citations
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Journal ArticleDOI
Identification of continuous-time systems
G.P. Rao,Heinz Unbehauen +1 more
TL;DR: Continuous-time model-based system identification as mentioned in this paper is a well-established field in the field of control systems and is concerned with the determination of particular models for systems that are intended for a certain purpose such as control.
Book
Identification of Continuous-Time Systems: Linear and Robust Parameter Estimation
TL;DR: In this article, Allamaraju Subrahmanyam and Ganti Prasada Rao consider continuous-time systems and propose robust methods of estimating the parameters of these systems.
Journal ArticleDOI
A Microprocessor-Based System for On-Line Parameter Identification in Continuous Dynamical Systems
Ganti Prasada Rao,Dines Chandra Saha,Tatapudi Mallikarjuna Rao,Krishnan Aghoramurthy,Amit Bhaya +4 more
TL;DR: A microprocessor-based unit for online identification of the parameters in linear continuous lumped dynamical systems is proposed which implements an algorithm which uses the so-called Poisson mement functionals of input-output data from the actual process under identification.
Journal ArticleDOI
Linear System Identification via Poisson Moment Functionals
Lawrence A. Bergman,A. L. Halet +1 more
Proceedings ArticleDOI
A recursive identification method for continuous time-varying linear systems
Z.H. Jiang,W. Schaufelberger +1 more
TL;DR: In this paper, a method for online identification of continuous time-varying linear systems is proposed based on the block pulse functions, where simple regression equations corresponding to the original differential equation models with time varying parameters can be obtained, and algorithms developed in discrete-time model identification can be applied directly to estimate the time changing parameters without much modification.
References
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Journal ArticleDOI
Identification of deterministic time-lag systems
Ganti Prasada Rao,L. Sivakumar +1 more
TL;DR: In this article, the authors extend the capability of the class of methods to cover time-lag systems, which is illustrated with reference to one of the methods that employs Poisson moment functionals.
Journal ArticleDOI
Parameter identification for linear time-varying dynamic processes
F.W. Fairman,D.W.C. Shen +1 more
TL;DR: In this paper, the authors present a method for determining the parameters of a process whose behaviour can be modelled by a linear differential equation with time-varying coefficients in the form of finite-order polynomials.
Journal ArticleDOI
Time domain synthesis via Poisson moment functionals
TL;DR: In this article, the authors present a method of time-domain synthesis of dynamical systems treating the process signals as distributions or generalized functions, in the manner originally established by L. Schwartz.
Journal ArticleDOI
Parameter identification for a class of multivariable non-linear processes
TL;DR: In this article, a new signal processing technique is presented and applied to the problem of determining the parameters of processes whose dynamic behaviour is characterized by a set of ordinary first-order non-linear differential equations.