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Adaptive Self-Learning Fuzzy Autopilot Design for Uncertain Bank-to-Turn Missiles
Rong, Hai-Jun1; Yang, Zhao-Xu1; Wong, Pak Kin2; Vong, Chi Man3
2017-04
Source PublicationJOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME
ISSN0022-0434
Volume139Issue:4
Abstract

This paper proposes an adaptive self-learning fuzzy autopilot design for uncertain bankto-turn (BTT) missiles due to external disturbances and system errors from the variations of the aerodynamic coefficients and control surface loss. The self-learning fuzzy systems called extended sequential adaptive fuzzy inference systems (ESAFISs) are utilized to compensate for these uncertainties in an adaptive backstepping architecture. ESAFIS is a real-time self-learning fuzzy system with simultaneous structure identification and parameter learning. The fuzzy rules of the ESAFIS can be added or deleted based on the input data. Based on the Lyapunov stability theory, adaptation laws are derived to update the consequent parameters of fuzzy rules, which guarantees both tracking performance and stability. The robust control terms with the adaptive boundestimation schemes are also designed to compensate for modeling errors of the ESAFISs by augmenting the self-learning fuzzy autopilot control laws. The proposed autopilot is validated under the control surface loss, aerodynamic parameter perturbations, and external disturbances. Simulation study is also compared with a conventional backstepping autopilot and a neural autopilot in terms of the tracking ability. The results illustrate that the designed fuzzy autopilot can obtain better steady-state and transient performance with the dynamically self-learning ability.

DOI10.1115/1.4035091
URLView the original
Indexed BySCI
Language英语
WOS Research AreaAutomation & Control Systems ; Instruments & Instrumentation
WOS SubjectAutomation & Control Systems ; Instruments & Instrumentation
WOS IDWOS:000395187100002
PublisherASME
The Source to ArticleWOS
Fulltext Access
Citation statistics
Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Affiliation1.State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
2.Department of Electromechanical Engineering, University of Macau, Macau, China
3.Department of Computer and Information Science, University of Macau, Macau, China
Recommended Citation
GB/T 7714
Rong, Hai-Jun,Yang, Zhao-Xu,Wong, Pak Kin,et al. Adaptive Self-Learning Fuzzy Autopilot Design for Uncertain Bank-to-Turn Missiles[J]. JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME,2017,139(4).
APA Rong, Hai-Jun,Yang, Zhao-Xu,Wong, Pak Kin,&Vong, Chi Man.(2017).Adaptive Self-Learning Fuzzy Autopilot Design for Uncertain Bank-to-Turn Missiles.JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME,139(4).
MLA Rong, Hai-Jun,et al."Adaptive Self-Learning Fuzzy Autopilot Design for Uncertain Bank-to-Turn Missiles".JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME 139.4(2017).
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