Model Reference Tracking Control Solutions for a Visual Servo System Based on a Virtual State from Unknown Dynamics

Model Reference Tracking Control Solutions for a Visual Servo System Based on a Virtual State from Unknown Dynamics

This paper focuses on validating a model-free Value Iteration Reinforcement Learning (MFVI-RL) control solution on a visual servo tracking system in a comprehensive manner starting from theoretical convergence analysis to detailed hardware and software implementation. Learning is based on a virtual...

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Bibliographic Details
Main Authors: Timotei Lala, Darius-Pavel Chirla, Mircea-Bogdan Radac
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Energies
Subjects:
reinforcement learning and approximate dynamic programming
virtual state feedback reference tuning
model reference control
unknown dynamics
input-output observable system
visual servo
Online Access:https://www.mdpi.com/1996-1073/15/1/267

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https://www.mdpi.com/1996-1073/15/1/267

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