Trajectory Planning and Adaptive Control architecture for increasing autonomy of UCAV in strike missions

Chang Qing Wang, Hong Shi Lu, Yang Shu, Ai Jun Li, Rooh Ul Amin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The Autonomous Trajectory Planning and Adaptive Control (ATPAC) architecture is proposed in this paper to achieve UCAV autonomous navigation during strike mission with unknown threats. The ATPAC architecture is consisted of a navigation module and a flight control module. The navigation module is implemented by policy-gradient learning algorithm coupled with expectant direction search (EDS) strategy which is introduced in this paper. The flight control module implemented by Structure Adaptive Model Inverse (SAMI) algorithm, which can cope with significant parameter uncertainties of the vehicle's mathematic model and maintain adequate flight performance of the vehicle. Combat scenario is presented to test the performance of the ATPAC architecture for a UCAV.

Original languageEnglish
Title of host publicationCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages103-109
Number of pages7
ISBN (Electronic)9781467383189
DOIs
StatePublished - 20 Jan 2017
Event7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016 - Nanjing, Jiangsu, China
Duration: 12 Aug 201614 Aug 2016

Publication series

NameCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

Conference

Conference7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
Country/TerritoryChina
CityNanjing, Jiangsu
Period12/08/1614/08/16

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