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Stochastic optimal control of quasi non-integrable Hamiltonian systems with stochastic maximum principle

机译:具有随机最大值原理的拟非积分哈密顿系统的随机最优控制

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摘要

A new procedure for designing optimal control of quasi non-integrable Hamiltonian systems under stochastic excitations is proposed based on the stochastic averaging method for quasi non-integrable Hamiltonian systems and the stochastic maximum principle. First, the control problem consisting of 2n-dimensional equations governing the controlled quasi non-integrable system and performance index is converted into a partially averaged one consisting of one-dimensional equation of the controlled system and performance index by using the stochastic averaging method. Then, the adjoint equation and the maximum condition of the partially averaged control problem are derived based on the stochastic maximum principle. The optimal control forces are determined from the maximum condition and solving the forward-backward stochastic differential equations (FBSDE). For infinite time-interval ergodic control, the adjoint variable is a stationary process and the FBSDE is reduced to a partial differential equation. Finally, the response statistics of optimally controlled system is predicted by solving the Fokker-Plank equation (FPE) associated with the fully averaged It? equation of the controlled system. An example of two degree-of-freedom (DOF) quasi non-integrable Hamiltonian system is worked out to illustrate the proposed procedure and its effectiveness.
机译:基于拟非积分哈密顿系统的随机平均方法和随机极大原理,提出了一种在随机激励下设计拟非积分哈密顿系统最优控制的新程序。首先,通过使用随机平均方法,将由控制准拟不可积分系统和性能指标的2n维方程组成的控制问题转换为由受控系统的一维方程和性能指标组成的部分平均的控制问题。然后,基于随机极大值原理推导了伴随方程和部分平均控制问题的极大值条件。最佳控制力是根据最大条件确定的,并且可以求解向前-向后随机微分方程(FBSDE)。对于无限时间间隔遍历控制,伴随变量是平稳过程,FBSDE简化为偏微分方程。最后,通过求解与完全平均It?相关的Fokker-Plank方程(FPE)来预测最优控制系统的响应统计量。受控系统的方程。以两自由度拟不可积分哈密顿系统为例,说明了所提出的程序及其有效性。

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