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Response of dynamic systems to renewal impulse processes: Generating equation for moments based on the integro-differential Chapman-Kolmogorov equations

机译:动态系统对更新脉冲过程的响应:基于积分微分Chapman-Kolmogorov方程生成矩方程

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In the present paper the method is developed for the derivation of differential equations for statistical moments of the state vector (response) of a non-linear dynamic system subjected to a random train of impulses. The arrival times of the impulses are assumed to be driven by a non-Poisson counting process. The state vector of the dynamic system is then a non-Markov process and no method is directly available for the derivation of the equations for response moments. The original non-Markov problem is converted into a Markov one by recasting the excitation process with the aid of an auxiliary, pure-jump stochastic process characterized by a Markov chain. Hence the conversion is carried out at the expense of augmentation of the state space of the dynamic system by auxiliary Markov states. For the augmented problem the sets of forward and backward integro-differential Chapman-Kolmogorov equations are formulated. The general, generating equation for moments is obtained with the aid of the forward and backward integro-differential Chapman-Kolmogorov operators. The developed method is illustrated by the examples of several renewal impulse processes.
机译:在本文中,开发了一种方法,用于推导非线性系统在随机脉冲作用下的状态向量(响应)的统计矩的微分方程。假设脉冲的到达时间是由非泊松计数过程驱动的。于是,动态系统的状态向量是一个非马尔可夫过程,并且没有直接可用于推导响应力矩方程的方法。通过在以马尔可夫链为特征的辅助纯跃变随机过程的帮助下重塑激发过程,将原始的非马尔可夫问题转化为马尔可夫问题。因此,以辅助马尔可夫状态来增加动态系统的状态空间为代价来进行转换。对于扩展问题,制定了正向和反向积分微分Chapman-Kolmogorov方程组。借助于向前和向后的积分微分Chapman-Kolmogorov算子可以得到矩的一般生成方程。几种更新脉冲过程的例子说明了所开发的方法。

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