Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model

Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads th...

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Bibliographic Details
Main Authors: Izzat Al-Darraji, Dimitrios Piromalis, Ayad A. Kakei, Fazal Qudus Khan, Milos Stojemnovic, Georgios Tsaramirsis, Panagiotis G. Papageorgas
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Electronics
Subjects:
aerial robot arms
modeling of aerial robot arms
adaptive controller
robust controller
sliding mode controller
RBF neural network
Online Access:https://www.mdpi.com/2079-9292/10/7/831

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https://www.mdpi.com/2079-9292/10/7/831

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