Response and Stability of a Random Differential Equation: Part II—Expansion Method

1989 ◽  
Vol 56 (1) ◽  
pp. 196-201 ◽  
Author(s):  
H. Benaroya ◽  
M. Rehak
Keyword(s):  
Differential Equation ◽  
White Noise ◽  
Colored Noise ◽  
Expansion Method ◽  
Approximate Expression ◽  
Companion Paper ◽  
Random Coefficients ◽  
Random Input ◽  
Linear Stochastic Differential Equation ◽  
Random Differential Equation

A linear stochastic differential equation of order N with colored noise random coefficients and random input is studied. An approximate expression for the autocorrelation of the response is derived in terms of the statistical properties of the random coefficients and input. This is achieved by using an expansion method known as the Born expansion (Feynman, 1962). Feynman diagrams are used as a short hand notation. In the particular case where the coefficients are white noise processes, the expansion method yields identical results to those obtained using an alternate method in a companion paper (Benaroya and Rehak, 1989). The expansion method is also used to demonstrate that white noise coefficients are statistically uncorrelated from the response.

Response and Stability of a Random Differential Equation: Part I—Moment Equation Method

1989 ◽  
Vol 56 (1) ◽  
pp. 192-195 ◽  
Author(s):  
H. Benaroya ◽  
M. Rehak
Keyword(s):  
Differential Equation ◽  
Autocorrelation Function ◽  
Moment Equation ◽  
Random Force ◽  
Random Coefficients ◽  
Closed Form Solutions ◽  
Linear Stochastic Differential Equation ◽  
Random Differential Equation ◽  
Stability Bound ◽  
Present Solution

A linear stochastic differential equation of order N excited by an external random force and whose coefficients are white noise random processes is studied. The external force may be either white or colored noise random process. Given the statistical properties of the coefficients and of the force, equivalent statistics are obtained for the response. The present solution method is based on the derivation of the equation governing the response autocorrelation function. The simplifying assumption that the response is stationary when the coefficients and input force are stationary is introduced. Another simplification occurs with the assumption that the response is uncorrelated from the random coefficients. Closed-form solutions for the response autocorrelation function and spectral density are derived in conjunction with a stability bound.

RANDOM DIFFERENTIAL EQUATIONS WITH RANDOM DELAYS

2011 ◽  
Vol 11 (02n03) ◽  
pp. 369-388 ◽  
Author(s):  
M. J. GARRIDO-ATIENZA ◽  
A. OGROWSKY ◽  
B. SCHMALFUSS
Keyword(s):  
Dynamical System ◽  
Differential Equation ◽  
Existence And Uniqueness ◽  
Existence Result ◽  
Random Dynamical System ◽  
Random Delay ◽  
Random Differential Equation ◽  
Autonomous Case ◽  
Random Differential Equations ◽  
Uniqueness Of A Solution

We investigate a random differential equation with random delay. First the non-autonomous case is considered. We show the existence and uniqueness of a solution that generates a cocycle. In particular, the existence of an attractor is proved. Secondly we look at the random case. We pay special attention to the measurability. This allows us to prove that the solution to the random differential equation generates a random dynamical system. The existence result of the attractor can be carried over to the random case.

An Analytical Scheme for Stochastic Dynamic Systems Containing Fractional Derivatives

1999 ◽  
Author(s):  
Om P. Agrawal
Keyword(s):  
White Noise ◽  
Expansion Method ◽  
Stochastic Dynamic ◽  
Stochastic Response ◽  
Analytical Technique ◽  
Analytical Scheme ◽  
Damped System ◽  
Duhamel Integral ◽  
General Response ◽  
Stochastic Dynamic Systems

Abstract This paper presents an analytical technique for the analysis of a stochastic dynamic system whose damping behavior is described by a fractional derivative of order 1/2. In this approach, an eigenvector expansion method proposed by Suarez and Shokooh is used to obtain the response of the system. The properties of Laplace transforms of convolution integrals are used to write a set of general Duhamel integral type expressions. The general response contains two parts, namely zero state and zero input. For a stochastic analysis the input force is treated as a random process with specified mean and correlation functions. An expectation operator is applied on a set of expressions to obtain the stochastic characteristics of the system. Closed form stochastic response expressions are obtained for white noise. Numerical results are presented to show the stochastic response of a fractionally damped system subjected to white noise.

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