单自由度摩擦系统离散模型

发展了两种随机离散数学模型:导出了一个以二维平均映射描述的随机模型,并建立了一个概率预报模型.通过实例对不同模型进行了比较,对于平均映射模型,分岔图指出了外噪声对系统性质的影响,通过符号动力学方法分析指出概率预报模型的随机性质.     

Evaluation of the growth rate of the state vector in a second-order generalized linear stochastic system

A second-order generalized linear stochastic dynamical system is considered. The entries of the system matrix are assumed to be independent and exponentially distributed. Evaluation of the growth rate of the system state vector is reduced to algebraic computations which involve solving an algebraic linear system and evaluating a linear functional for the solution.     

Input-output behaviour of a stochastic Galerkin method for a low pass filter

We apply the stochastic Galerkin method to a linear dynamical system, which includes random variables to quantify uncertainties in physical parameters. The input-output behaviour of the stochastic Galerkin system is described by a transfer function in the frequency domain. The importance of each output component can be estimated by Hardy norms. We investigate a Hardy norm in the case of a linear dynamical system modelling the electric circuit of a low pass filter. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A formula for the lyapunov numbers of a stochastic flow. application to a perturbation theorem

We present a formula for the Lyapunov exponents of the flow of a nonlinear stochastic system. (These exponents characterise the asymptotic behaviour of the derivative flow, and negative exponents are associated with clustering of the flow). This formula is analogous to that of Khas'minskii, who deals with a linear system. We use this fojoruila to show that if we have an ordinary dynamical system which is Lyapunov stable (i.e. all the exponents are negative) then so are certain stochastic perturbations of it.     

Dynamical Analysis for a General Jerky Equation with Random Excitation

A general jerky equation with random excitation is investigated in this paper. Before introducing the random excitation term, the equation is reduced to a two-dimensional model when undergoing a Hopf bifurcation. Then the model with the parametric excitation and external excitation is converted to a stochastic differential equation with singularity based on the stochastic average theory. For the equation, its dynamical behaviors are analyzed in different parameters'' spaces, including the stability, stochastic bifurcation and stationary solution. Besides, numerical simulations are given to show the asymptotic behavior of the stationary solution.     

Stochastic discrete Hamiltonian variational integrators

Variational integrators are derived for structure-preserving simulation of stochastic Hamiltonian systems with a certain type of multiplicative noise arising in geometric mechanics. The derivation is based on a stochastic discrete Hamiltonian which approximates a type-II stochastic generating function for the stochastic flow of the Hamiltonian system. The generating function is obtained by introducing an appropriate stochastic action functional and its corresponding variational principle. Our approach permits to recast in a unified framework a number of integrators previously studied in the literature, and presents a general methodology to derive new structure-preserving numerical schemes. The resulting integrators are symplectic; they preserve integrals of motion related to Lie group symmetries; and they include stochastic symplectic Runge–Kutta methods as a special case. Several new low-stage stochastic symplectic methods of mean-square order 1.0 derived using this approach are presented and tested numerically to demonstrate their superior long-time numerical stability and energy behavior compared to nonsymplectic methods.     

Effect of the phase on the dynamics of a perturbed bouncing ball system

The phase control method is a non-feedback control technique which has been used for different purposes in continuous periodically driven dynamical systems. One of the main goals of this paper is to apply this control technique to the bouncing ball system, which can be seen as a paradigmatic periodically driven discrete dynamical system, and has a rather simple physical interpretation. The main idea is to apply a periodic control signal including a phase difference with respect to the periodic forcing of the initial system and to analyze its effect on the dynamics of the bouncing ball system. The numerical simulations we have carried out clearly show the strong effect of the phase of the control signal in suppressing or generating chaotic behavior and in changing the period of a periodic orbit. We have also analyzed the effect of the phase in the phenomenon of the crisis-induced intermittency, showing how the phase enhances the size of the attractor near a crisis and can induce the intermittent behavior. Finally we have analyzed the scaling behavior of the crisis by varying the phase difference between the perturbation and the external forcing.     

带刚性限位的双层隔振系统的离散随机模型

研究由多刚体组成的带刚性限位的双层隔振系统,对其冲击后受到周期性外激励和低强度噪声扰动共同作用下可能会产生的碰撞进行了分析．基于单向约束多体动力学理论,导出了此隔振系统的最大Poincaré映射,建立了其冲击后的零次近似随机离散模型和一次近似随机离散模型．通过对一MTU公司的柴油机隔振系统冲击作用后振动响应的调查指出,由于可能发生间歇性碰撞,该系统呈现复杂的非线性特性．零次近似模型和一次近似模型有较大的区别,低强度的噪声也会对系统产生较大的影响．得到的结果对如何正确设计带刚性限位的双层隔振系统提供了理论参考依据．     

Numerical optimization of certain dynamical stochastic systems

Two-dimensional dynamical (dynamical stochastic) predator-prey systems are optimized numerically by calculating the variation of the functional of the steady-state solution to the Fokker-Plank equation. Numerical algorithms are used to construct systems with a prescribed response to a certain external action.     

Symmetry-breaking bifurcation analysis of stochastic van der pol system via Chebyshev polynomial approximation

Chebyshev polynomial approximation is applied to the symmetry-breaking bifurcation problem of a stochastic van der Pol system with bounded random parameter subjected to harmonic excitation. The stochastic system is reduced into an equivalent deterministic system, of which the responses can be obtained by numerical methods. Nonlinear dynamical behaviors related to various forms of stochastic bifurcations in stochastic system are explored and studied numerically.     

Evaluation of the growth rate of the state vector in a generalized linear stochastic system

A second-order generalized linear stochastic dynamical system is considered. The entries of the system matrix are assumed to be independent and exponentially distributed. In order to evaluate the mean rate of growth of the system state vector, a sequence of one-dimensional probability distributions is introduced. Derivation of the limiting density function is reduced to solving a linear algebraic system. The density is used for evaluation of the mean rate of growth for the system under study.     

Strong convergence of a stochastic Rosenbrock-type scheme for the finite element discretization of semilinear SPDEs driven by multiplicative and additive noise

This paper aims to investigate the numerical approximation of a general second order parabolic stochastic partial differential equation(SPDE) driven by multiplicative and additive noise. Our main interest is on such SPDEs where the nonlinear part is stronger than the linear part, usually called stochastic dominated transport equations. Most standard numerical schemes lose their good stability properties on such equations, including the current linear implicit Euler method. We discretize the SPDE in space by the finite element method and propose a novel scheme called stochastic Rosenbrock-type scheme for temporal discretization. Our scheme is based on the local linearization of the semi-discrete problem obtained after space discretization and is more appropriate for such equations. We provide a strong convergence of the new fully discrete scheme toward the exact solution for multiplicative and additive noise and obtain optimal rates of convergence. Numerical experiments to sustain our theoretical results are provided.     

随机能源Logistic反馈控制系统的分岔研究

建立了非线性随机动力模型—带噪声的能源Logistic反馈控制模型,应用随机平均法对随机动力模型进行了简化,得到了一个二维的扩散过程.二维过程满足Ito型随机微分方程,应用不变测度理论研究了该模型的随机分岔.最后,给出了数值实验验证了相应的结论.     

On the dynamic reconstruction of the input of a control system

We consider the problem of reconstructing the right-hand side of a dynamical system subjected to external disturbances. Under the assumption that the states of the system are measured with some error, we indicate an algorithm for solving the problem on the basis of the method of auxiliary positional control models. The algorithm is stable under noises and numerical errors.     

Reconstruction of random-disturbance amplitude in linear stochastic equations from measurements of some of the coordinates

The problem of reconstructing the unknown amplitude of a random disturbance in a linear stochastic differential equation is studied in a fairly general formulation by applying dynamic inversion theory. The amplitude is reconstructed using discrete information on several realizations of some of the coordinates of the stochastic process. The problem is reduced to an inverse one for a system of ordinary differential equations satisfied by the elements of the covariance matrix of the original process. Constructive solvability conditions in the form of relations on the parameters of the system are discussed. A finite-step software implementable solving algorithm based on the method of auxiliary controlled models is tested using a numerical example. The accuracy of the algorithm is estimated with respect to the number of measured realizations.     

Distributionally robust parameter identification of a time-delay dynamical system with stochastic measurements

In this paper, we consider a parameter identification problem involving a time-delay dynamical system, in which the measured data are stochastic variable. However, the probability distribution of this stochastic variable is not available and the only information we have is its first moment. This problem is formulated as a distributionally robust parameter identification problem governed by a time-delay dynamical system. Using duality theory of linear optimization in a probability space, the distributionally robust parameter identification problem, which is a bi-level optimization problem, is transformed into a single-level optimization problem with a semi-infinite constraint. By applying problem transformation and smoothing techniques, the semi-infinite constraint is approximated by a smooth constraint and the convergence of the smooth approximation method is established. Then, the gradients of the cost and constraint functions with respect to time-delay and parameters are derived. On this basis, a gradient-based optimization method for solving the transformed problem is developed. Finally, we present an example, arising in practical fermentation process, to illustrate the applicability of the proposed method.     

Integration of mussel in fish farm: Mathematical model and analysis

The paper deals with the dynamical behavior of fish and mussel population in a fish farm where external food is supplied. The ecosystem of the fish farm is represented by a set of nonlinear differential equations involving the nutrient (food), fish and mussels. We have studied the boundedness, local stability and global stability of the model system. We have incorporated the discrete type gestational delay of fish and analyze effect of the delay on the dynamical behavior of the model system. The delay parameter complicates the dynamics depending on the external food from changing the stable state to unstable damped periodic trajectories leading to a limit cycle oscillation. We have studied the Hopf-bifurcation of the model system in the neighborhood of the coexisting equilibrium point considering delay as a variable bifurcation parameter. We have performed numerical simulation to verify the analytical results. The entire study reveals that the external food supply controls the dynamics of the system.     

Evolving to the edge of chaos: Chance or necessity?

We show that ecological systems evolve to edges of chaos (EOC). This has been demonstrated by analyzing three diverse model ecosystems using numerical simulations in combination with analytical procedures. It has been found that all these systems reside on EOC and display short-term recurrent chaos (strc). The first two are non-linear food chains and the third one is a linear food chain. The dynamics of first two is dictated by deterministic changes in system parameters. In contrast to this, dynamics of the third model system (the linear food chain) is governed by both deterministic changes in system parameters as well as exogenous stochastic perturbations (unforeseen changes in initial conditions) of these dynamical systems.     

Short-term memories with a stochastic perturbation

We investigate short-term memories in linear and weakly nonlinear coupled map lattices with a periodic external input. We use locally coupled maps to present numerical results about short-term memory formation adding a stochastic perturbation in the maps and in the external input.