随机 2-D Roesser 模型的线性二次优化控制

IF 5.4 3区材料科学 Q2 CHEMISTRY, PHYSICAL ACS Applied Energy Materials Pub Date : 2024-08-28 DOI:10.1016/j.matcom.2024.08.029

Xiaomin Xue , Juanjuan Xu , Huanshui Zhang

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引用次数: 0

摘要

本文研究了具有乘法噪声的 Roesser 模型所控制的随机二维（2-D）系统的线性二次（LQ）最优控制问题。本文的主要贡献在于通过提出一组新颖的前向和后向随机偏微分方程（FBSPDE），给出了必要和充分的最优性条件，并分别基于类里卡蒂差分方程和代数方程，进一步提出了有限视界和无限视界上的显式最优反馈控制律。还提供了一些数值模拟来说明所设计控制器的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Linear quadratic optimal control of stochastic 2-D Roesser models

This paper investigates the linear quadratic (LQ) optimal control problem for the stochastic two-dimensional (2-D) systems governed by Roesser models with multiplicative noise. The main contribution is to give the necessary and sufficient optimality condition by proposing a set of novel forward and backward stochastic partial difference equations (FBSPDE), and to further present the explicitly optimal feedback control laws on the finite horizon and on the infinite horizon based on the Riccati-like difference equations and the algebraic equation, respectively. Several numerical simulations are provided to illustrate the performance of the designed controllers.

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来源期刊

ACS Applied Energy Materials Materials Science-Materials Chemistry

CiteScore

10.30

自引率

6.20%

发文量

1368

期刊介绍： ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.