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Piecewise Constant Orthogonal Functions and Their Application to Systems and Control
TLDR
In this article, the authors proposed piecewise constant orthogonal basis functions (PCF) for linear and non-linear linear systems, and the optimal control of linear lag-free and time-lag systems.Abstract:
I Piecewise constant orthogonal basis functions.- II Operations on square integrable functions in terms of PCBF spectra.- III Analysis of lumped continuous linear systems.- IV Analysis of time delay systems.- V Solution of functional differential equations.- VI Analysis of non-linear and time-varying systems.- VII Optimal control of linear lag-free systems.- VIII Optimal control of time-lag systems.- IX Solution of partial differential equations (PDE) [W55].- X Identification of continuous lumped parameter systems.- XI Parameter identification in distributed systems.read more
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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.
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Numerical solution of nonlinear Fredholm integral equations of the second kind using Haar wavelets
TL;DR: A computational method for solving nonlinear Fredholm integral equations of the second kind which is based on the use of Haar wavelets is presented, which shows efficiency of the method.
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A review of identification in continuous-time systems
Heinz Unbehauen,G.P. Rao +1 more
TL;DR: A birds eye view of the continuous-time related aspects of the greater field of system identification is presented and some recent developments in the identification of linear systems and nonlinear systems are outlined.
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Numerical solution of integral equations system of the second kind by block-pulse functions
TL;DR: The characteristic of Block–Pulse functions is described and it is indicated that through this method a system of Fredholm integral equations can be reduced to an algebraic equation.
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Numerical solution of stochastic Volterra integral equations by a stochastic operational matrix based on block pulse functions
TL;DR: By using block pulse functions and their stochastic operational matrix of integration, a stochastically Volterra integral equation can be reduced to a linear lower triangular system, which can be directly solved by forward substitution.