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Distribution Modeling and Stabilization Control for Discrete-Time Linear Random Dynamical Systems Using Ensemble Kalman Filter

2019/04/10 by Yohei Hosoe, Dimitri Peaucelle, Hosoe, Yohei +1
Computer Science · Engineering · #FOS: Electrical engineering #Fault Detection and Control Systems #Stability and Controllability of Differential Equations #Systems and Control (eess.SY) #Target Tracking and Data Fusion in Sensor Networks #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.1904.05030

openalex publication_date 2019/04/10 · openalex created_date 2019/04/25 · openalex updated_date 2026/07/28

Abstract

This paper studies an output feedback stabilization control framework for discrete-time linear systems with stochastic dynamics determined by an independent and identically distributed (i.i.d.) process. The controller is constructed with an ensemble Kalman filter (EnKF) and a feedback gain designed with our earlier result about state feedback control. The EnKF is also used for modeling the distribution behind the system, which is required in the feedback gain synthesis. The effectiveness of our control framework is demonstrated with numerical experiments. This study will become the first step toward the realization of learning type control using our stochastic systems control theory.

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