Neural control for longitudinal dynamics of hypersonic aircraft

Bin Xu, Zhongke Shi, Danwei Wang, Han Wang, Senqiang Zhu

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

Abstract

This paper investigated the discrete adaptive controller with neural network for the longitudinal dynamics of a generic hypersonic flight vehicle. Based on functional decomposition, we design the controller for the altitude subsystem and the velocity subsystem separately. The altitude subsystem is transformed into the explicit 4-step ahead prediction model with four 1-step ahead prediction subsequences. The control design is based on the state feedback and neural approximation. For each subsystem only one neural network is employed to approximate the lumped system uncertainty. The controller is considerably simpler than the ones based on back-stepping scheme. The velocity subsystem is transformed into the output feedback form and the indirect discrete NN controller is applied. The semiglobal uniform ultimate boundedness stability and the output tracking error are made within a neighborhood of zero. The simulation is presented to show the effectiveness of the proposed control approach.

Original languageEnglish
Title of host publication2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings
PublisherIEEE Computer Society
Pages993-998
Number of pages6
ISBN (Print)9781479908172
DOIs
StatePublished - 2013
Event2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Atlanta, GA, United States
Duration: 28 May 201328 May 2013

Publication series

Name2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013 - Conference Proceedings

Conference

Conference2013 International Conference on Unmanned Aircraft Systems, ICUAS 2013
Country/TerritoryUnited States
CityAtlanta, GA
Period28/05/1328/05/13

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