Neural-Assisted Synthesis of a Linear Quadratic Controller for Applications in Active Suspension Systems of Wheeled Vehicles

Neural-Assisted Synthesis of a Linear Quadratic Controller for Applications in Active Suspension Systems of Wheeled Vehicles

This article presents a neural algorithm based on Reinforcement Learning for optimising Linear Quadratic Regulator (LQR) creation. The proposed method allows designing such a target function that automatically leads to changes in the quality and resource matrix so that the target LQR regulator achie...

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Bibliographic Details
Main Authors: Mateusz Kozek, Adam Smoter, Krzysztof Lalik
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Energies
Subjects:
LQR
neural networks
optimal control
MIMO systems
suspension control
active suspension system
Online Access:https://www.mdpi.com/1996-1073/16/4/1677

Internet

https://www.mdpi.com/1996-1073/16/4/1677

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