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A nonlinear stochastic optimal bounded control using stochastic maximum principle

机译:基于随机最大值原理的非线性随机最优有界控制

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摘要

A nonlinear stochastic optimal bounded control strategy for quasi-Hamiltonian systems with actuator saturation is proposed based on the stochastic averaging method and stochastic maximum principle. First, the averaged Ito stochastic differential equations are derived by using the stochastic averaging method for quasi-Hamiltonian systems. Then, the stochastic Hamiltonian system for optimal control with a given performance index is established based on the stochastic maximum principle. The bounded optimal control consisting of unbounded optimal control and bounded bang-bang control is determined by solving the forward-backward stochastic differential equations with control constraint. Finally, three examples of quasi-Hamiltonian systems with controls are given to illustrate the application of the proposed strategy. Numerical results show that the proposed control strategy significantly improves the control efficiency and chattering attenuation of the corresponding bang-bang control.
机译:基于随机平均方法和随机最大原理,提出了一种具有执行器饱和的拟哈密顿系统的非线性随机最优有界控制策略。首先,采用准哈密顿系统的随机平均方法,推导了平均的伊藤随机微分方程。然后,基于随机最大原理,建立了具有给定性能指标的随机汉密尔顿最优控制系统。通过求解带控制约束的前向-后向随机微分方程,可以确定由无界最优控制和有界爆炸控制组成的有界最优控制。最后,给出了带有控制的准哈密顿系统的三个例子,以说明所提出策略的应用。数值结果表明,所提出的控制策略显着提高了相应爆炸控制的控制效率和抖振衰减。

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