Decentralized control for optimal LQ problems in stochastic systems with unknown uncertainties

IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
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引用次数: 0

Abstract

In this paper, we study the optimal control problem of a linear quadratic stochastic system where the randomness results from multiplicative noises. Especially, two controllers having access to different information are involved in the system. Different from most of the existing results which are based on the condition that the information of multiplicative noise is known during the design of optimal controllers, we focus on a more general case that the statistical information of the multiplicative noise is inaccessible. Under this setting, we propose a stochastic approximation algorithm to derive the solutions to algebraic Riccati equations (AREs) and obtain the optimal and stabilizing decentralized controllers.
具有未知不确定性的随机系统中最优 LQ 问题的分散控制
本文研究了一个线性二次随机系统的最优控制问题,该系统的随机性来自乘法噪声。特别是,系统中涉及两个获取不同信息的控制器。与大多数基于在设计最优控制器时已知乘法噪声信息的现有结果不同,我们关注的是无法获取乘法噪声统计信息的更一般情况。在这种情况下,我们提出了一种随机近似算法来推导代数里卡提方程(ARE)的解,并获得最优和稳定的分散控制器。
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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来源期刊
CiteScore
7.30
自引率
14.60%
发文量
586
审稿时长
6.9 months
期刊介绍: The Journal of The Franklin Institute has an established reputation for publishing high-quality papers in the field of engineering and applied mathematics. Its current focus is on control systems, complex networks and dynamic systems, signal processing and communications and their applications. All submitted papers are peer-reviewed. The Journal will publish original research papers and research review papers of substance. Papers and special focus issues are judged upon possible lasting value, which has been and continues to be the strength of the Journal of The Franklin Institute.
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