Neural Network Control of a Parallel Hybrid-electric Propulsion System for a Small Unmanned Aerial Vehicle

Neural Network Control of a Parallel Hybrid-electric Propulsion System for a Small Unmanned Aerial Vehicle
Author :
Publisher :
Total Pages : 566
Release :
ISBN-10 : UCAL:X70999
ISBN-13 :
Rating : 4/5 (99 Downloads)

Book Synopsis Neural Network Control of a Parallel Hybrid-electric Propulsion System for a Small Unmanned Aerial Vehicle by : Frederick G. Harmon

Download or read book Neural Network Control of a Parallel Hybrid-electric Propulsion System for a Small Unmanned Aerial Vehicle written by Frederick G. Harmon and published by . This book was released on 2005 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles (UAVs) used for military, homeland security, and disaster monitoring missions involving intelligence, surveillance, or reconnaissance (ISR). The benefits include increased time-on-station and range than electric-powered UAVs and stealth modes not available with gasoline-powered UAVs. A conceptual design of a small UAV with a parallel hybrid-electric propulsion system, an optimization routine for the energy use, the application of a neural network to approximate the optimization results, and simulation results are provided. The two-point conceptual design includes an internal combustion engine sized for cruise and an electric motor and lithium-ion battery pack sized for endurance speed. The flexible optimization routine allows relative importance to be assigned between the use of gasoline, electricity, and recharging. The Cerebellar Model Arithmetic Computer (CMAC) neural network approximates the optimization results and is applied to the control of the parallel hybrid-electric propulsion system. The CMAC controller saves on the required memory compared to a large look-up table by two orders of magnitude. The energy use for the hybrid-electric UAV with the CMAC controller during a one-hour and a three-hour ISR mission is 58% and 27% less, respectively, than for a gasoline-powered UAV.


Neural Network Control of a Parallel Hybrid-electric Propulsion System for a Small Unmanned Aerial Vehicle Related Books

Neural Network Control of a Parallel Hybrid-electric Propulsion System for a Small Unmanned Aerial Vehicle
Language: en
Pages: 566
Authors: Frederick G. Harmon
Categories:
Type: BOOK - Published: 2005 - Publisher:

DOWNLOAD EBOOK

Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles (UAVs) used for military, homeland security, and disaster mon
Drones - Various Applications
Language: en
Pages: 258
Authors: Dragan Cvetković
Categories: Technology & Engineering
Type: BOOK - Published: 2024-02-07 - Publisher: BoD – Books on Demand

DOWNLOAD EBOOK

Although many believe that unmanned aerial vehicles or drones are a recent invention, unmanned flight has a rich history that goes all the way back to ancient t
Hybrid Technologies for Power Generation
Language: en
Pages: 530
Authors: Massimiliano Lo Faro
Categories: Science
Type: BOOK - Published: 2021-10-30 - Publisher: Academic Press

DOWNLOAD EBOOK

Hybrid Technologies for Power Generation addresses the topics related to hybrid technologies by coupling conventional thermal engines with novel technologies, i
Hydrogen Electrical Vehicles
Language: en
Pages: 276
Authors: Mehmet Sankir
Categories: Science
Type: BOOK - Published: 2023-03-21 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

HYDROGEN ELECTRICAL VEHICLES Hydrogen electrical vehicles are an essential component of the “Green New Deal” and this book covers cutting-edge technologies
Analysis and Simulation of Electrical and Computer Systems
Language: en
Pages: 444
Authors: Damian Mazur
Categories: Technology & Engineering
Type: BOOK - Published: 2017-10-20 - Publisher: Springer

DOWNLOAD EBOOK

This book addresses selected topics in electrical engineering, electronics and mechatronics that have posed serious challenges for both the scientific and engin