Article

 

Genetic Fuzzy Trees and their Application Towards Autonomous Training and Control of a Squadron of Unmanned Combat Aerial Vehicles Open Access Deposited

Downloadable Content

Download PDF
Download Adobe Acrobat Reader
Date Uploaded: 02/03/2017
Date Modified: 04/05/2017

This study introduces the technique of Genetic Fuzzy Trees (GFTs) through novel application to an air combat control problem of an autonomous squadron of Unmanned Combat Aerial Vehicles (UCAVs) equipped with next-generation defensive systems. GFTs are a natural evolution to Genetic Fuzzy Systems, in which multiple cascading fuzzy systems are optimized by genetic methods. In this problem a team of UCAV's must traverse through a battle space and counter enemy threats, utilize imperfect systems, cope with uncertainty, and successfully destroy critical targets. Enemy threats take the form of Air Interceptors (AIs), Surface to Air Missile (SAM) sites, and Electronic WARfare (EWAR) stations. Simultaneous training and tuning a multitude of Fuzzy Inference Systems (FISs), with varying degrees of connectivity, is performed through the use of an optimized Genetic Algorithm (GA). The GFT presented in this study, the Learning Enhanced Tactical Handling Algorithm (LETHA), is able to create controllers with the presence of deep learning, resilience to uncertainties, and adaptability to changing scenarios. These resulting deterministic fuzzy controllers are easily understandable by operators, are of very high performance and efficiency, and are consistently capable of completing new and different missions not trained for.

Creator
License
Submitter
College
Department
Date Created
Language
Note
  • This work was part of a pilot "mediated-deposit model" where library staff found potential works, later submitted for faculty review

Digital Object Identifier (DOI)

Identifier: 10.1142/S2301385015500120
Link: http://dx.doi.org/10.1142/S2301385015500120

This DOI link is the best way for others to cite your work.

Relationships

Items

Permanent link to this page: https://scholar.uc.edu/show/bc386s86w