The first-passage problem of dynamical power system of a single-machine-infinite-bus (SMIB) system under random perturbations is studied.First,the stochastic averaging method for quasi non-integrable generalized Hamiltonian systems is applied to reduce the equations of the SMIB system under random perturbations to a set of averaged It equations.Then,the backward Kolmogorov equation governing the conditional reliability function and the Pontryagin equation governing the conditional mean of first passage time are established and solved numerically,respectively.Finally,the proposed method is verified by using the Monte Carlo simulation of the original system.
CHEN LinCong1 & ZHU WeiQiu2 1 College of Civil Engineering,Huaqiao University,Xiamen 361021,China
The approximate transient response of quasi integrable Hamiltonian systems under Gaussian white noise excitations is investigated. First, the averaged Ito equations for independent motion integrals and the associated Fokker-Planck-Kolmogorov (FPK) equation governing the transient probability density of independent motion integrals of the system are derived by applying the stochastic averaging method for quasi integrable Hamiltonian systems. Then, approximate solution of the transient probability density of independent motion integrals is obtained by applying the Galerkin method to solve the FPK equation. The approximate transient solution is expressed as a series in terms of properly selected base functions with time-dependent coefficients. The transient probability densities of displacements and velocities can be derived from that of independent motion integrals. Three examples are given to illustrate the application of the proposed procedure. It is shown that the results for the three examples obtained by using the proposed procedure agree well with those from Monte Carlo simulation of the original systems.
A response analysis procedure is developed for a vibro-impact system excited by colored noise.The non-smooth transformation is used to convert the vibro-impact system into a new system without impact term.With the help of the modified quasi-conservative averaging,the total energy of the new system can be approximated as a Markov process,and the stationary probability density function(PDF)of the total energy is derived.The response PDFs of the original system are obtained using the analytical solution of the stationary PDF of the total energy.The validity of the theoretical results is tested through comparison with the corresponding simulation results.Moreover,stochastic bifurcations are also explored.
This paper deals with the approximate nonstationary probability density of a class of nonlinear vibrating system excited by colored noise.First,the stochastic averaging method is adopted to obtain the averaged It equation for the amplitude of the system.The corresponding Fokker-Planck-Kolmogorov equation governing the evolutionary probability density function is deduced.Then,the approximate solution of the Fokker-Planck-Kolmogorov equation is derived by applying the Galerkin method.The solution is expressed as a sum of a series of expansion in terms of a set of proper basis functions with timedepended coefficients.Finally,an example is given to illustrate the proposed procedure.The validity of the proposed method is confirmed by Monte Carlo Simulation.
We studied the response of fractional-order van de Pol oscillator to Gaussian white noise excitation in this letter. An equivalent integral-order nonlinear stochastic system is obtained to replace the given system based on the principle of minimum mean-square error. Through stochastic averaging, an averaged Ito equation is deduced. We obtained the Fokker–Planck–Kolmogorov equation connected to the averaged Ito equation and solved it to yield the approximate stationary response of the system. The analytical solution is confirmed by using Monte Carlo simulation.
The classical Lotka–Volterra(LV) model is a well-known mathematical model for prey-predator ecosystems. In the present paper, the pulse-type version of stochastic LV model, in which the effect of a random natural environment has been modeled as Poisson white noise, is investigated by using the stochastic averaging method. The averaged generalized Ito stochastic differential equation and Fokker–Planck–Kolmogorov(FPK) equation are derived for prey-predator ecosystem driven by Poisson white noise. Approximate stationary solution for the averaged generalized FPK equation is obtained by using the perturbation method.The effect of prey self-competition parameter ε2s on ecosystem behavior is evaluated. The analytical result is confirmed by corresponding Monte Carlo(MC) simulation.
A stochastic optimal control strategy for a slightly sagged cable using support motion in the cable axial direction is proposed.The nonlinear equation of cable motion in plane is derived and reduced to the equations for the first two modes of cable vibration by using the Galerkin method.The partially averaged Ito equation for controlled system energy is further derived by applying the stochastic averaging method for quasi-non-integrable Hamiltonian systems.The dynamical programming equation for the controlled system energy with a performance index is established by applying the stochastic dynamical programming principle and a stochastic optimal control law is obtained through solving the dynamical programming equation.A bilinear controller by using the direct method of Lyapunov is introduced.The comparison between the two controllers shows that the proposed stochastic optimal control strategy is superior to the bilinear control strategy in terms of higher control effectiveness and efficiency.
