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Optimal control of a class of linear stochastic distributed-parameter systems

机译:一类线性随机分布参数系统的最优控制

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摘要

The paper treats the optimal distributed and boundary control problem for a general class of linear stochastic distributed-parameter systems. A quadratic cost functional is used, and the stochastic distributed Hamilton-Jacobi equation, which is derived by the dynamic-programming technique, is solved explicitly. Analogously to the lumped-parameter case, the result is a pair of linear optimal feedback controllers, their common weighting function being described by a matrix partial-integrodilferential equation of the Riccati form. When the state of the system is not exactly measured, the distributed Kalman's filter, derived in a recent paper, is used, the decoupling of the optimal controllers and the optimal estimator being proved. Kalman's duality principle is extended to the distributed systems under investigation, the canonical equations of Hamilton are derived and a version of Pontryagin's minimum principle is proved.
机译:本文讨论了一般一类线性随机分布参数系统的最优分布和边界控制问题。利用二次成本函数,通过动态规划技术推导了随机分布的Hamilton-Jacobi方程。类似于集总参数情况,结果是一对线性最优反馈控制器,它们的共同加权函数由Riccati形式的矩阵部分积分微分方程描述。当无法精确测量系统状态时,使用最近发表的分布式卡尔曼滤波器,证明了最优控制器和最优估计器之间的解耦。将卡尔曼对偶原理扩展到所研究的分布式系统,推导了汉密尔顿的正则方程,并证明了庞特里亚金最小原理的一种形式。

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