Parametric Vibration of Submerged Floating Tunnel Tether Under Random Excitation

For the study of the parametric vibration response of submerged floating tunnel tether under random excitation, a nonlinear random parametric vibration equation of coupled tether and tube of submerged floating tunnel is set up. Subsequently, vibration response of tether in the tether-tube system is analyzed by Monte Carlo method. It may be concluded that when the tube is subjected to zero-mean Gaussian white noise random excitation, the displacement and velocity root mean square responses of tether reach the peak if the circular frequency of tube doubles that of tether; the displacement and velocity root mean square responses of tether increase as the random excitation root mean square increases; owing to the damping force of water, the displacement and velocity root mean square responses of tether decrease rapidly compared with tether in air; increasing the damping of the tether or tube reduces the displacement and velocity root mean square responses of tether; the large-amplitude vibration of tether may be avoided by locating dampers on the tether or tube.

STOCHASTIC OPTIMAL CONTROL OF STRONGLY NONLINEAR SYSTEMS UNDER WIDE-BAND RANDOM EXCITATION WITH ACTUATOR SATURATION

A bounded optimal control strategy for strongly non-linear systems under non-white wide-band random excitation with actuator saturation is proposed. First, the stochastic averaging method is introduced for controlled strongly non-linear systems under wide-band random excitation using generalized harmonic functions. Then, the dynamical programming equation for the saturated control problem is formulated from the partially averaged Itō equation based on the dynamical programming principle. The optimal control consisting of the unbounded optimal control and the bounded bang-bang control is determined by solving the dynamical programming equation. Finally, the response of the optimally controlled system is predicted by solving the reduced Fokker-Planck-Kolmogorov （FPK） equation associated with the completed averaged Itō equation. An example is given to illustrate the proposed control strategy. Numerical results show that the proposed control strategy has high control effectiveness and efficiency and the chattering is reduced significantly comparing with the bang-bang control strategy.

Time-delayed feedback control optimization for quasi linear systems under random excitations

A strategy for time-delayed feedback control optimization of quasi linear systems with random excitation is proposed. First, the stochastic averaging method is used to reduce the dimension of the state space and to derive the stationary response of the system. Secondly, the control law is assumed to be velocity feedback control with time delay and the unknown control gains are determined by the performance indices. The response of the controlled system is predicted through solving the Fokker-Plank-Kolmogorov equation associated with the averaged Ito equation. Finally, numerical examples are used to illustrate the proposed control method, and the numerical results are confirmed by Monte Carlo simulation .

An iterative algorithm for analysis of coupled structural-acoustic systems subject to random excitations

This paper analyzes the random response of structural-acoustic coupled systems. Most existing works on coupled structural-acoustic analysis are limited to systems under deterministic excitations due to high computational cost required by a random response analysis. To reduce the computational burden involved in the coupled random analysis, an iterative procedure based on the Pseudo excitation method has been developed. It is found that this algorithm has an overwhelming advantage in computing efficiency over traditional methods, as demonstrated by some numerical examples given in this paper.

Complex response analysis of a non-smooth oscillator under harmonic and random excitations

It is well-known that practical vibro-impact systems are often influenced by random perturbations and external excitation forces,making it challenging to carry out the research of this category of complex systems with non-smooth characteristics.To address this problem,by adequately utilizing the stochastic response analysis approach and performing the stochastic response for the considered non-smooth system with the external excitation force and white noise excitation,a modified conducting process has proposed.Taking the multiple nonlinear parameters,the non-smooth parameters,and the external excitation frequency into consideration,the steady-state stochastic P-bifurcation phenomena of an elastic impact oscillator are discussed.It can be found that the system parameters can make the system stability topology change.The effectiveness of the proposed method is verified and demonstrated by the Monte Carlo(MC)simulation.Consequently,the conclusions show that the process can be applied to stochastic non-autonomous and non-smooth systems.

Modeling and parameter identification of linear time-varying systems based on adaptive chirplet transform under random excitation

In this paper,a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying(LTV)systems under random excitation is presented.It is assumed that the solution of responses of LTV structures is expressed as the sum of multicomponent Linear Frequency Modulated(LFM)signals in a short-time.Then the measured acceleration response is used to perform the adaptive chirplet transform,in which an integral algorithm is employed to reconstruct the velocity and displacement responses.The vibration differential equation with time-varying coefficients is transformed into a simple linear equation.Furthermore,for systems under random excitation,the input–output relation based on correlation function is also derived to estimate the parameters including physicals parameters and instantaneous modal parameters.The full procedure of the method is presented and validated by using simulated responses.The results show that the presented method is accurate and robust for various LTV systems under random excitation.

Dynamic Characteristics of Tracked Vehicle Power Train Considering Road Random Torsional Excitation

The road random torsional excitation is one type of torque rooted from the road roughness and vehicle drive system. This paper aims to study how the road random torsional excitation affects the dynamic characteristics of vehicle power train. The method of simulating the random torsional excitation of tracked vehicle is explored at first. Secondly,the road random torsional excitations under different road roughness,vehicle speeds and pre-tensions are obtained. Thirdly,the dynamic analysis model of tracked vehicle power train is constructed with the consideration of the road random torsional excitation. Eventually,the influences of this excitation on output torque,bearing support force,vibration acceleration and dynamic shear stress of transmission shafts are intensively studied.The research conclusions are helpful to correct and refine the present virtual prototype of tracked vehicle power train.

Analysis on Pseudo Excitation of Random Vibration for Structure of Time Flight Counter

Traditional computing method is inefficient for getting key dynamical parameters of complicated structure.Pseudo Excitation Method（PEM）is an effective method for calculation of random vibration.Due to complicated and coupling random vibration in rocket or shuttle launching,the new staging white noise mathematical model is deduced according to the practical launch environment.This deduced model is applied for PEM to calculate the specific structure of Time of Flight Counter（ToFC）.The responses of power spectral density and the relevant dynamic characteristic parameters of ToFC are obtained in terms of the flight acceptance test level.Considering stiffness of fixture structure,the random vibration experiments are conducted in three directions to compare with the revised PEM.The experimental results show the structure can bear the random vibration caused by launch without any damage and key dynamical parameters of ToFC are obtained.The revised PEM is similar with random vibration experiment in dynamical parameters and responses are proved by comparative results.The maximum error is within 9%.The reasons of errors are analyzed to improve reliability of calculation.This research provides an effective method for solutions of computing dynamical characteristic parameters of complicated structure in the process of rocket or shuttle launching.

Karhunen-loéve expansion for random earthquake excitations

This paper develops a trigonometric-basis-fimction based Karhunen-Loeve （KL） expansion for simulating random earthquake excitations with known covariance functions. The methods for determining the number of the KL terms and defining the involved random variables are described in detail. The simplified form of the KL expansion is given, whereby the relationship between the KL expansion and the spectral representation method is investigated and revealed. The KL expansion is of high efficiency for simulating long-term earthquake excitations in the sense that it needs a minimum number of random variables, as compared with the spectral representation method. Numerical examples demonstrate the convergence and accuracy of the KL expansion for simulating two commonly-used random earthquake excitation models and estimating linear and nonlinear random responses to the random excitations.

Dynamics and response reshaping of nonlinear predator-prey system undergoing random abrupt disturbances

An actual ecological predator-prey system often undergoes random environmental mutations owing to the impact of natural disasters and man-made destruction, which may destroy the balance between the species. In this paper,the stochastic dynamics of the nonlinear predator-prey system considering random environmental mutations is investigated, and a feedback control strategy is proposed to reshape the response of the predator-prey system against random abrupt environmental mutations. A delayed Markov jump system(MJS) is established to model such a predator-prey system. A novel first integral is constructed which leads to better approximation solutions of the ecosystem. Then, by applying the stochastic averaging method based on this novel first integral, the stochastic response of the predator-prey system is investigated, and an analytical feedback control is designed to reshape the response of the ecosystem from the disturbed state back to the undisturbed one.Numerical simulations finally illustrate the accuracy and effectiveness of the proposed procedure.

NONLINEAR RANDOM STABILITY OF VISCOELASTIC CABLE WITH SMALL CURVATURE

The nonlinear planar mean square response and the random stability of a viscoelastic cable that has a small curvature and subjects to planar narrow band random excitation is studied. The Kelvin viscoelastic constitutive model is chosen to describe the viscoelastic property of the cable material. A mathematical model that describes the nonlinear planar response of a viscoelastic cable with small equilibrium curvature is presented first. And then a method of investigating the mean square response and the almost sure asymptotic stability of the response solution is presented and regions of instability are charted. Finally , the almost sure asymptotic stability condition of a viscoelastic cable with small curvature under narrow band excitation is obtained.

Modeling and Analysis of a Random Excited Double-Clamped Piezoelectric Energy Harvester

A double-clamped piezoelectric energy harvester subjected to random excitation is presented,for which corresponding analytical model is established to predict its output characteristics.With the presented theoretical natural frequency and equivalent stiffness of vibrator,the closed-form expressions of mean power and voltage acquired from the double-clamped piezoelectric energy harvester under random excitation are derived.Finally theoretical analysis is conducted for the output performance of the doubleclamped energy harvester with the change of spectrum density（SD）of acceleration,load resistance,piezoelectric coefficient and natural frequency value,which is found to closely agree with Monte Carlo simulation and experimental results.

Synchronization performance in time-delayed random networks induced by diversity in system parameter

Synchronization rhythm and oscillating in biological systems can give clues to understanding the cooperation and competition between cells under appropriate biological and physical conditions. As a result, the network setting is appreciated to detect the stability and transition of collective behaviors in a network with different connection types. In this paper, the synchronization performance in time-delayed excitable homogeneous random networks（EHRNs） induced by diversity in system parameters is investigated by calculating the synchronization parameter and plotting the spatiotemporal evolution pattern, and distinct impacts induced by parameter-diversity are detected by setting different time delays. It is found that diversity has no distinct effect on the synchronization performance in EHRNs with small time delay being considered. When time delay is increased greatly, the synchronization performance of EHRN degenerates remarkably as diversity is increased. Surprisingly, by setting a moderate time delay, appropriate parameter-diversity can promote the synchronization performance in EHRNs, and can induce the synchronization transition from the asynchronous state to the weak synchronization. Moreover, the bistability phenomenon, which contains the states of asynchronous state and weak synchronization,is observed. Particularly, it is confirmed that the parameter-diversity promoted synchronization performance in time-delayed EHRN is manifested in the enhancement of the synchronization performance of individual oscillation and the increase of the number of synchronization transitions from the asynchronous state to the weak synchronization. Finally, we have revealed that this kind of parameter-diversity promoted synchronization performance is a robust phenomenon.

Dynamic responses of an energy harvesting system based on piezoelectric and electromagnetic mechanisms under colored noise

Because of the increasing demand for electrical energy,vibration energy harvesters(VEHs)that convert vibratory energy into electrical energy are a promising technology.In order to improve the efficiency of harvesting energy from environmental vibration,here we investigate a hybrid VEH.Unlike previous studies,this article analyzes the stochastic responses of the hybrid piezoelectric and electromagnetic energy harvesting system with viscoelastic material under narrow-band(colored)noise.Firstly,a mass-spring-damping system model coupled with piezoelectric and electromagnetic circuits under fundamental acceleration excitation is established,and analytical solutions to the dimensionless equations are derived.Then,the formula of the amplitude-frequency responses in the deterministic case and the first-order and secondorder steady-state moments of the amplitude in the stochastic case are obtained by using the multi-scales method.The amplitude-frequency analytical solutions are in good agreement with the numerical solutions obtained by the Monte Carlo method.Furthermore,the stochastic bifurcation diagram is plotted for the first-order steady-state moment of the amplitude with respect to the detuning frequency and viscoelastic parameter.Eventually,the influence of system parameters on mean-square electric voltage,mean-square electric current and mean output power is discussed.Results show that the electromechanical coupling coefficients,random excitation and viscoelastic parameter have a positive effect on the output power of the system.

STOCHASTIC OPTIMAL VIBRATION CONTROL OF PARTIALLY OBSERVABLE NONLINEAR QUASI HAMILTONIAN SYSTEMS WITH ACTUATOR SATURATION

An optimal vibration control strategy for partially observable nonlinear quasi Hamiltonian systems with actuator saturation is proposed. First,a controlled partially observable non-linear system is converted into a completely observable linear control system of finite dimension based on the theorem due to Charalambous and Elliott. Then the partially averaged It stochastic differential equations and dynamical programming equation associated with the completely observable linear system are derived by using the stochastic averaging method and stochastic dynamical programming principle,respectively. The optimal control law is obtained from solving the final dynamical programming equation. The results show that the proposed control strategy has high control effectiveness and control effciency.

The Parametric Identification of a System with Unclear Input information

This paper develops an average power and energy method for the parametric identification of a system. The new method makes it possible to identify the parameters of a system depending only on its output information, and can be used in both linear and non-linear systems.

VEHICLE DYNAMIC ANALYSIS SIMULATION－MODELLING THEORY AND ENGINEERING APPLICATION

A computer software named VDAS (Vehicle Dynamic Analysis Simulation) is presented.Based on the mathematical modelling for a military vehicle as a 3-D dynamic system, the softwarecreates random excitation resulting from double side road-surface roughness by statisticalsimulation, and solves for the time series of the system response from the system state equations,and gives out the results in probability statistics as well as performance evaluations.

Contrastive Analysis of General and Special Forced Oscillations of Power Systems

With the continuous incorporation of renewable energy and new loads into the electric power grid,random factors that induce general forced oscillations(GFOs)gradually become risks that affect the power system's security and stability.T his research conducts a comparative analysis of the generation mechanisms of GFOs versus the traditional special forced oscillations(SFOs),specifically,from the perspective of frequency domain.Similarities and differences in en-oscillating conditions,occurrence probabilities,and the influencing factors of GFO and SFO are compared to better understand and recognize the GFO theory and the response characteristics of the power system under random excitations.A series of simulations in the lO-generator,39-bus New England Test System is carried out to verify the analysis.

An efficient stochastic dynamic analysis of soil media using radial basis function artificial neural network

Since a lot of engineering problems are along with uncertain parameters, stochastic methods are of great importance for incorporating random nature of a system property or random nature of a system input. In this study, the stochastic dynamic analysis of soil mass is performed by finite element method in the frequency domain. Two methods are used for stochastic analysis of soil media which are spectral decomposition and Monte Carlo methods. Shear modulus of soil is considered as a random field and the seismic excitation is also imposed as a random process. In this research, artificial neural network is proposed and added to Monte Carlo method for sake of reducing computational effort of the random analysis. Then, the effects of the proposed artificial neural network are illustrated on decreasing computational time of Monte Carlo simulations in comparison with standard Monte Carlo and spectral decomposition methods. Numerical verifications are provided to indicate capabilities, accuracy and efficiency of the proposed strategy compared to the other techniques.