Feedforward–Feedback Controller Based on a Trained Quaternion Neural Network Using a Generalised <inline-formula><math display="inline"><semantics><mi mathvariant="double-struck">HR</mi></semantics></math></inline-formula> Calculus with Application to Trajectory Control of a Three-Link Robot Manipulator

Feedforward–Feedback Controller Based on a Trained Quaternion Neural Network Using a Generalised <inline-formula><math display="inline"><semantics><mi mathvariant="double-struck">HR</mi></semantics></math></inline-formula> Calculus with Application to Trajectory Control of a Three-Link Robot Manipulator

This study derives a learning algorithm for a quaternion neural network using the steepest descent method extended to quaternion numbers. This applies the generalised Hamiltonian–Real calculus to obtain derivatives of a real–valued cost function concerning quaternion variables and designs a feedback...

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Bibliographic Details
Main Authors: Kazuhiko Takahashi, Eri Tano, Masafumi Hashimoto
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Machines
Subjects:
hypercomplex numbers
quaternion neural network
generalised Hamiltonian–Real calculus
feedforward–feedback controller
robot manipulator
Online Access:https://www.mdpi.com/2075-1702/10/5/333

Internet

https://www.mdpi.com/2075-1702/10/5/333

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