On Time Domain Identification and Sensitivity Analysis Using Orthogonal Functions

1999 ◽  
Author(s):  
Ricardo P. Pacheco ◽  
Valder Steffen
Keyword(s):  
Sensitivity Analysis ◽  
Jacobi Polynomials ◽  
Operational Matrix ◽  
Algebraic Equations ◽  
Chebyshev Series ◽  
Unknown Parameters ◽  
Orthogonal Functions ◽  
Domain Identification ◽  
Second Order Differential Equations ◽  
Block Pulse Functions

Abstract Orthogonal functions can be integrated using a so-called operational matrix. This characteristic transforms a set of second order differential equations into algebraic equations which are easily solved. In the case of mechanical systems the unknown parameters can be determined from these algebraic equations. For this purpose, the input and output signals have to be expanded in time orthogonal functions. This technique can be also applied for sensitivity analysis. In this paper Fourier series, Legendre polynomials, Jacobi polynomials, Chebyshev series, Block-Pulse functions and Walsh functions are used to expand the signals as time functions.

Using Orthogonal Functions for Identification and Sensitivity Analysis of Mechanical Systems

2002 ◽  
Vol 8 (7) ◽  
pp. 993-1021 ◽  
Author(s):  
R. P. Pacheco ◽  
V. Steffen
Keyword(s):  
Sensitivity Analysis ◽  
Initial Conditions ◽  
Structural Parameters ◽  
Operational Matrix ◽  
Mechanical Systems ◽  
Algebraic Equations ◽  
Unknown Parameters ◽  
Orthogonal Functions ◽  
In Series ◽  
Operational Matrix Of Integration

Differential equations can be transformed into algebraic equations by using an integration property of the orthogonal functions and the so-called operational matrix of integration. In this way, the calculation effort performed by the identification process or sensitivity analysis of mechanical systems can be reduced. For this purpose, mechanical systems are represented by state-space equations and the input and output signals are developed in series of orthogonal functions. After the integration of these equations a simple set of algebraic equations is obtained, which leads to the determination of the unknown parameters, such as modal and structural parameters, excitation forces, initial conditions and sensitivity functions. Different orthogonal functions were tested in numerical and experimental applications, including gyroscopic systems.

Stochastic operational matrix of Chebyshev wavelets for solving multi-dimensional stochastic Itô–Volterra integral equations

2019 ◽  
Vol 17 (03) ◽  
pp. 1950007 ◽  
Author(s):  
S. Singh ◽  
S. Saha Ray
Keyword(s):  
Integral Equations ◽  
Numerical Solutions ◽  
General Procedure ◽  
Operational Matrix ◽  
Volterra Integral Equations ◽  
Algebraic Equations ◽  
Chebyshev Wavelets ◽  
System Of Integral Equations ◽  
Block Pulse Functions ◽  
Stochastic Operational Matrix

In this paper, the numerical solutions of multi-dimensional stochastic Itô–Volterra integral equations have been obtained by second kind Chebyshev wavelets. The second kind Chebyshev wavelets are orthonormal and have compact support on [Formula: see text]. The block pulse functions and their relations to second kind Chebyshev wavelets are employed to derive a general procedure for forming stochastic operational matrix of second kind Chebyshev wavelets. The system of integral equations has been reduced to a system of nonlinear algebraic equations and solved for obtaining the numerical solutions. Convergence and error analysis of the proposed method are also discussed. Furthermore, some examples have been discussed to establish the accuracy and efficiency of the proposed scheme.

scholarly journals Systems of nonlinear Volterra integro-differential equations of arbitrary order

2018 ◽  
Vol 36 (4) ◽  
pp. 33-54 ◽  
Author(s):  
Kourosh Parand ◽  
Mehdi Delkhosh
Keyword(s):  
Differential Equations ◽  
Fractional Derivative ◽  
Approximate Method ◽  
Fractional Order ◽  
Chebyshev Polynomials ◽  
Arbitrary Order ◽  
Operational Matrix ◽  
Algebraic Equations ◽  
Arbitrary Integer ◽  
Orthogonal Functions

In this paper, a new approximate method for solving of systems of nonlinear Volterra integro-differential equations of arbitrary (integer and fractional) order is introduced. For this purpose, the generalized fractional order of the Chebyshev orthogonal functions (GFCFs) based on the classical Chebyshev polynomials of the first kind has been introduced that can be used to obtain the solution of the integro-differential equations (IDEs). Also, we construct the fractional derivative operational matrix of order $\alpha$ in the Caputo's definition for GFCFs. This method reduced a system of IDEs by collocation method into a system of algebraic equations. Some examples to illustrate the simplicity and the effectiveness of the propose method have been presented.

scholarly journals Solving of Linear Volterra-Fredholm Integral Equations via Modification of Block Pulse Functions

2021 ◽  
Vol 17 (1) ◽  
pp. 33
Author(s):  
Ayyubi Ahmad
Keyword(s):  
Approximate Solution ◽  
Integral Equations ◽  
Operational Matrix ◽  
Approximate Solutions ◽  
Computational Method ◽  
Fredholm Integral Equations ◽  
Triangular System ◽  
Algebraic Equations ◽  
Block Pulse Functions ◽  
Linear Algebraic Equations

A computational method based on modification of block pulse functions is proposed for solving numerically the linear Volterra-Fredholm integral equations. We obtain integration operational matrix of modification of block pulse functions on interval [0,T). A modification of block pulse functions and their integration operational matrix can be reduced to a linear upper triangular system. Then, the problem under study is transformed to a system of linear algebraic equations which can be used to obtain an approximate solution of  linear Volterra-Fredholm integral equations. Furthermore, the rate of convergence is  O(h) and error analysis of the proposed method are investigated. The results show that the approximate solutions have a good of efficiency and accuracy.

scholarly journals Improved Block-Pulse Functions for Numerical Solution of Mixed Volterra-Fredholm Integral Equations

Axioms ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 200
Author(s):  
Ji-Huan He ◽  
Mahmoud H. Taha ◽  
Mohamed A. Ramadan ◽  
Galal M. Moatimid
Keyword(s):  
Linear System ◽  
Computer Program ◽  
Integral Equations ◽  
Operational Matrix ◽  
Basis Functions ◽  
Fredholm Integral Equations ◽  
Algebraic Equations ◽  
Numerical Examples ◽  
Block Pulse Functions ◽  
Operational Matrix Of Integration

The present paper employs a numerical method based on the improved block–pulse basis functions (IBPFs). This was mainly performed to resolve the Volterra–Fredholm integral equations of the second kind. Those equations are often simplified into a linear system of algebraic equations through the use of IBPFs in addition to the operational matrix of integration. Typically, the classical alterations have enhanced the time taken by the computer program to solve the system of algebraic equations. The current modification works perfectly and has improved the efficiency over the regular block–pulse basis functions (BPF). Additionally, the paper handles the uniqueness plus the convergence theorems of the solution. Numerical examples have been presented to illustrate the efficiency as well as the accuracy of the method. Furthermore, tables and graphs are used to show and confirm how the method is highly efficient.

scholarly journals Some Algorithms for Solving Third-Order Boundary Value Problems Using Novel Operational Matrices of Generalized Jacobi Polynomials

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
W. M. Abd-Elhameed
Keyword(s):  
Boundary Value Problems ◽  
Jacobi Polynomials ◽  
Boundary Value ◽  
Operational Matrix ◽  
Operational Matrices ◽  
Algebraic Equations ◽  
Third Order ◽  
Generalized Jacobi Polynomials ◽  
Nonlinear Algebraic Equations ◽  
Derivatives Of

The main aim of this research article is to develop two new algorithms for handling linear and nonlinear third-order boundary value problems. For this purpose, a novel operational matrix of derivatives of certain nonsymmetric generalized Jacobi polynomials is established. The suggested algorithms are built on utilizing the Galerkin and collocation spectral methods. Moreover, the principle idea behind these algorithms is based on converting the boundary value problems governed by their boundary conditions into systems of linear or nonlinear algebraic equations which can be efficiently solved by suitable solvers. We support our algorithms by a careful investigation of the convergence analysis of the suggested nonsymmetric generalized Jacobi expansion. Some illustrative examples are given for the sake of indicating the high accuracy and efficiency of the two proposed algorithms.

Numerical solutions for fractional initial value problems of distributed-order

2021 ◽  
pp. 2150096
Author(s):  
M. A. Abdelkawy
Keyword(s):  
Fractional Order ◽  
Initial Value Problem ◽  
Numerical Solutions ◽  
Jacobi Polynomials ◽  
Algebraic Equations ◽  
Initial Value ◽  
Orthogonal Functions ◽  
Jacobi Functions ◽  
Distributed Order ◽  
Numerical Approaches

This paper addresses spectral collocation techniques to treat with the fractional initial value problem of distributed-order. We introduce three algorithms based on shifted fractional order Jacobi orthogonal functions outputted by Jacobi polynomials. The shifted fractional order Jacobi–Gauss–Radau collocation method is developed for approximating the fractional initial value problem of distributed-order. The principal target in our techniques is to transform the fractional initial value problem of distributed-order to a system of algebraic equations. Some numerical examples are given to test the accuracy and applicability of our technique. It is known that the accuracy of numerical approaches for nonsmooth solution is deteriorated. Employing fractional order Jacobi functions instead of the classical Jacobi stopped this deterioration.

Numerical solution of Riccati equation using operational matrix method with Chebyshev polynomials

2015 ◽  
Vol 08 (02) ◽  
pp. 1550020
Author(s):  
Yalçın Öztürk ◽  
Mustafa Gülsu
Keyword(s):  
Approximate Solution ◽  
Riccati Equation ◽  
Chebyshev Polynomials ◽  
Matrix Method ◽  
Numerical Technique ◽  
Operational Matrix ◽  
Algebraic Equations ◽  
Chebyshev Series ◽  
Numerical Examples ◽  
Operational Matrix Method

In this paper, we present numerical technique for solving the Riccati equation by using operational matrix method with Chebyshev polynomials. The method consists of expanding the required approximate solution as truncated Chebyshev series. Using operational matrix method, we reduce the problem to a set of algebraic equations. Some numerical examples are given to demonstrate the validity and applicability of the method. The method is easy to implement and produces very accurate results.

Solution of fractional oscillator equations using ultraspherical wavelets

2019 ◽  
Vol 16 (05) ◽  
pp. 1950075
Author(s):  
Firdous A. Shah ◽  
Rustam Abass
Keyword(s):  
Operational Matrix ◽  
Mathematical Physics ◽  
Test Problems ◽  
Algebraic Equations ◽  
Block Pulse Functions ◽  
Fractional Oscillator ◽  
Oscillator Type ◽  
General Order ◽  
Model Equations ◽  
Oscillator Equations

Fractional oscillator type equations are well-known model equations to describe several phenomenon in mathematical physics, engineering and biology. In this paper, a new method incorporated by the ultraspherical wavelet operational matrix of general order integration and block-pulse functions are adopted to investigate the solution of fractional oscillator type equations. To facilitate this, the ultraspherical wavelets are first presented and the corresponding operational matrix of fractional-order integration is derived by virtue of block pulse functions. The properties of ultraspherical wavelets and block pulse functions are used to transform the underlying problem to a system of algebraic equations which can be easily solved by any of the usual numerical methods. The efficiency and accuracy of the proposed method is demonstrated by presenting several benchmark test problems. Moreover, special attention is given to the comparison of the numerical results obtained by the new algorithm with those found by other known methods.

Parameter Estimation of Delay Systems Via Block Pulse Functions

1980 ◽  
Vol 102 (3) ◽  
pp. 159-162 ◽  
Author(s):  
Yen-Ping Shin ◽  
Chyi Hwang ◽  
Wei-Kong Chia
Keyword(s):  
Linear Time ◽  
Delay Systems ◽  
Algebraic Equations ◽  
Unknown Parameters ◽  
Linear Time Invariant ◽  
Least Squares Estimate ◽  
Block Pulse Functions ◽  
Linear Algebraic Equations ◽  
Delay Differential ◽  
Time Invariant

Linear time-invariant delay-differential equation systems are approximately represented by a set of linear algebraic equations with the block pulse functions. A least squares estimate is then used to determine the unknown parameters. Examples with satisfactory results are given.

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