Symbolic and numeric scheme for solution of linear integro-differential equations with random parameter uncertainties and Gaussian stochastic process input

Abstract

To cite this version:Igor E. Poloskov, Christian Soize. Symbolic and numeric scheme for solution of linear integrodifferential equations with random parameter uncertainties and Gaussian stochastic process input. Applied Mathematical Modelling, Elsevier, 2018, 56, pp.15-31 AbstractThe paper describes a theoretical apparatus and an algorithmic part of application of the Green matrix-valued functions for time-domain analysis of systems of linear stochastic integro-differential equations. It is suggested that these systems are subjected to Gaussian nonstationary stochastic noises in the presence of model parameter uncertainties that are described in the framework of the probability theory. If the uncertain model parameter is fixed to a given value, then a time-history of the system will be fully represented by a second-order Gaussian vector stochastic process whose properties are completely defined by its conditional vector-valued mean function and matrix-valued covariance function. The scheme that is proposed is constituted of a combination of two subschemes. The first one explicitly defines closed relations for symbolic and numeric computations of the conditional mean and covariance functions, and the second one calculates unconditional characteristics by the Monte Carlo method. A full scheme realized on the base of Wolfram Mathematica and Intel Fortran software programs, is demonstrated by an example devoted to an estimation of a nonstationary stochastic response of a mechanical system with a thermoviscoelastic component. Results obtained by using the proposed scheme are compared with a reference solution constructed by using a direct Monte Carlo simulation.

Dynamic output feedback control for a walking assistance training robot to handle shifts in the center of gravity and time-varying arm of force in omniwheel

“…where e 1 > 0; e 2 > 0; e 3 > 0; e 4 > 0; and e 5 > 0 are designed parameters. Substituting equations (19) to (23) into equation 18, the following can be obtained…”

“…22 However, these methods only consider the random vibration in the input channels (external disturbances). Another study 23 was conducted to investigate a symbolic and numeric scheme to solve linear differential equations with random parameter uncertainties. However, few results regarding nonlinear dynamic systems with the internal random parameters have been reported.…”