Bio-inspired adaptive fuzzy control systems for precise low-altitude hovering of an unmanned aerial vehicle under large uncertainties

Fendy Santoso, Matthew A. Garratt, Sreenatha G Anavatti, Jiefei Wang, Vu Phi Tran, M Meftahul Ferdaus

Research output: Book chapter/Published conference paperConference paperpeer-review

Abstract

The ability to learn and adapt to unknown system dynamics simplifies controller design and enables complex platforms to be controlled without the need to build complex mathematical models. Taking some inspiration from the way humans learn, we present the concept of bio-inspired self-learning in aerial robotics, leveraging on the concept of an adaptive Takagi-Sugeno (TS)-fuzzy control system. The main distinguishing feature of the evolving TS-fuzzy system is the ability to learn from scratch, eliminating the need to have a-priori knowledge about the system as in the traditional model-based control systems. Besides, the system can also learn from certain predefined rules. As opposed to traditional fuzzy systems, which require prior training (knowledge) to build their structure, the evolving TS-fuzzy system needs no such prior knowledge since the controller can perform online self-learning. Also, its ability to capture high-degree of uncertainties (e.g. severe ground effects due to low-altitude flying) is very advantageous. To demonstrate the efficacy of the control systems, we design and implement the evolving TS-fuzzy autopilots in the five control loops of our Tarot hexacopter drone after conducting extensive computer simulations using non-linear aerodynamics models. We also compare the efficacy of the autopilot systems with respect to the effectiveness of traditional PID controllers in the altitude control loop as a benchmark.
Original languageEnglish
Title of host publication2024 European Control Conference, ECC 2024
Place of PublicationStockholm, Sweden
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages3770-3775
Number of pages6
ISBN (Electronic)9783907144107
ISBN (Print)9798331540920
Publication statusPublished - 25 Jun 2024
Event22nd European Control Conference 2024: ECC24 - KTH Campus Valhallavägen, Stockholm, Sweden
Duration: 25 Jun 202428 Jun 2024
https://ecc24.euca-ecc.org/
https://ieeexplore.ieee.org/xpl/conhome/10590709/proceeding (Proceedings)
https://controls.papercept.net/conferences/conferences/ECC24/program/ (Program)

Publication series

Name2024 European Control Conference, ECC 2024

Conference

Conference22nd European Control Conference 2024
Country/TerritorySweden
CityStockholm
Period25/06/2428/06/24
OtherIt is our great pleasure to welcome you to Stockholm and the 22nd European Control Conference (ECC). This is the first time that ECC is held in Sweden. We are delighted to have the opportunity to host ECC 2024 on the KTH campus, inviting you to engage with academics and industry professionals from all over the world.
Internet address

Fingerprint

Dive into the research topics of 'Bio-inspired adaptive fuzzy control systems for precise low-altitude hovering of an unmanned aerial vehicle under large uncertainties'. Together they form a unique fingerprint.

Cite this