Approximate constrained stochastic optimal control via parameterized input inference

IF 4.8 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Shahbaz P. Qadri Syed, He Bai
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引用次数: 0

Abstract

Approximate methods to solve stochastic optimal control (SOC) problems have received significant interest from researchers in the past decade. Probabilistic inference approaches to SOC have been developed to solve nonlinear quadratic Gaussian problems. In this work, we propose an Expectation–Maximization (EM) based inference procedure to generate state-feedback controls for constrained SOC problems. We consider the inequality constraints for the state and controls and also the structural constraints for the controls. We employ barrier functions to address state and control constraints. We show that the expectation step leads to smoothing of the state-control pair while the maximization step on the non-zero subsets of the control parameters allows inference of structured stochastic optimal controllers. We demonstrate the effectiveness of the algorithm on unicycle obstacle avoidance and four-unicycle formation control examples. In these examples, we perform an empirical study on the parametric effect of barrier functions on the state constraint satisfaction. We also present a comparative study of smoothing algorithms on the performance of the proposed approach.
通过参数化输入推理实现近似受限随机最优控制
在过去十年中,解决随机最优控制(SOC)问题的近似方法受到了研究人员的极大关注。为解决非线性二次高斯问题,已经开发出了 SOC 的概率推理方法。在这项工作中,我们提出了一种基于期望最大化(EM)的推理程序,用于生成受约束 SOC 问题的状态反馈控制。我们考虑了状态和控制的不等式约束,以及控制的结构约束。我们采用障碍函数来解决状态和控制约束。我们证明,期望步骤会导致状态-控制对的平滑化,而控制参数非零子集上的最大化步骤允许推断结构化随机最优控制器。我们在单车避障和四单车编队控制示例中演示了该算法的有效性。在这些示例中,我们对障碍函数对状态约束满足的参数影响进行了实证研究。我们还介绍了平滑算法与所提方法性能的比较研究。
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来源期刊
Automatica
Automatica 工程技术-工程:电子与电气
CiteScore
10.70
自引率
7.80%
发文量
617
审稿时长
5 months
期刊介绍: Automatica is a leading archival publication in the field of systems and control. The field encompasses today a broad set of areas and topics, and is thriving not only within itself but also in terms of its impact on other fields, such as communications, computers, biology, energy and economics. Since its inception in 1963, Automatica has kept abreast with the evolution of the field over the years, and has emerged as a leading publication driving the trends in the field. After being founded in 1963, Automatica became a journal of the International Federation of Automatic Control (IFAC) in 1969. It features a characteristic blend of theoretical and applied papers of archival, lasting value, reporting cutting edge research results by authors across the globe. It features articles in distinct categories, including regular, brief and survey papers, technical communiqués, correspondence items, as well as reviews on published books of interest to the readership. It occasionally publishes special issues on emerging new topics or established mature topics of interest to a broad audience. Automatica solicits original high-quality contributions in all the categories listed above, and in all areas of systems and control interpreted in a broad sense and evolving constantly. They may be submitted directly to a subject editor or to the Editor-in-Chief if not sure about the subject area. Editorial procedures in place assure careful, fair, and prompt handling of all submitted articles. Accepted papers appear in the journal in the shortest time feasible given production time constraints.
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