Data Driven Linear Quadratic Gaussian Control Design

Data Driven Linear Quadratic Gaussian Control Design

The implementation of the Linear Quadratic Gaussian (LQG) scheme is often considered problematic as it requires a dynamic model of the system as a whole. The challenges come from state variables without a physical representation and the interference factors that affect the reading process. This pape...

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Bibliographic Details
Main Authors: Adi Novitarini Putri, Carmadi Machbub, Dimitri Mahayana, Egi Hidayat
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Optimal control
LQG
LSTM
state estimation
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/10064282/

Internet

https://ieeexplore.ieee.org/document/10064282/

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