Data-Driven Fuzzy Controller Design for Hypersonic Vehicle

被引：0

作者：

Bai, Jian-Ming ^{[1
,2
]}

Zhao, Guang-She ^{[3
]}

Rong, Hai-Jun ^{[1
]}

机构：

[1] Xi An Jiao Tong Univ, State Key Lab Strength & Vibrat Mech Struct, Shaanxi Key Lab Environm & Control Flight Vehicle, Sch Aerosp, Xian 710049, Peoples R China

[2] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Opt Direct & Pointing Tech Res Dept, Xian 710119, Shaanxi, Peoples R China

[3] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710049, Peoples R China

来源：

IEEE 20TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS / IEEE 16TH INTERNATIONAL CONFERENCE ON SMART CITY / IEEE 4TH INTERNATIONAL CONFERENCE ON DATA SCIENCE AND SYSTEMS (HPCC/SMARTCITY/DSS) | 2018年

关键词：

hypersonic vehicle; fuzzy systems; data driven controller; OS-Fuzzy-ELM; EXTREME LEARNING-MACHINE;

D O I：

10.1109/HPCC/SmartCity/DSS.2018.00275

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a data driven fuzzy controller for a generic hypersonic vehicle. The fuzzy systems with any bounded nonconstant piecewise continuous membership functions are introduced to reconstruct the unknown system dynamics without relying on the exact mathematical models. The control law is designed based on the reconstructed fuzzy models. The stability analysis of the whole control system is presented from the Lyapunov function and shows that the tracking errors converge to zero. In order to save online computation time, the fuzzy membership function parameters are determined based on the idea of the OS-Fuzzy-ELM algorithm by randomly assigning the values to them. The simulation results demonstrate the superior performance of the proposed controller.

引用

页码：1698 / 1703

页数：6

共 13 条

[1]

Austin KJ, 2001, JOINT 9TH IFSA WORLD CONGRESS AND 20TH NAFIPS INTERNATIONAL CONFERENCE, PROCEEDINGS, VOLS. 1-5, P2428, DOI 10.1109/NAFIPS.2001.944453

[2]

Huo Y., 2006, P AIAA GUID NAV CONT, P4690

[3] Self-evolving fuzzy model-based controller with online structure and parameter learning for hypersonic vehicle [J].

Rong, Hai-Jun ;

Yang, Zhao-Xu ;

Wong, Pak Kin ;

Vong, Chi Man ;

Zhao, Guang-She .

AEROSPACE SCIENCE AND TECHNOLOGY, 2017, 64 :1-15

[4] Adaptive fuzzy control of aircraft wing-rock motion [J].

Rong, Hai-Jun ;

Han, Sai ;

Zhao, Guang-She .

APPLIED SOFT COMPUTING, 2014, 14 :181-193

[5] FUZZY EXTREME LEARNING MACHINE FOR A CLASS OF FUZZY INFERENCE SYSTEMS [J].

Rong, Hai-Jun ;

Huang, Guang-Bin ;

Liang, Yong-Qi .

INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, 2013, 21 :51-61

[6] Online Sequential Fuzzy Extreme Learning Machine for Function Approximation and Classification Problems [J].

Rong, Hai-Jun ;

Huang, Guang-Bin ;

Sundararajan, N. ;

Saratchandran, P. .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2009, 39 (04) :1067-1072

[7] FUZZY IDENTIFICATION OF SYSTEMS AND ITS APPLICATIONS TO MODELING AND CONTROL [J].

TAKAGI, T ;

SUGENO, M .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1985, 15 (01) :116-132

[8] Adaptive fuzzy neural network control design via a T-S fuzzy model for a robot manipulator including actuator dynamics [J].

Wai, Rong-Jong ;

Yang, Zhi-Wei .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2008, 38 (05) :1326-1346

[9] Robust nonlinear control of a hypersonic aircraft [J].

Wang, Q ;

Stengel, RF .

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2000, 23 (04) :577-585

[10] Nonlinear disturbance observer based robust backstepping control for a flexible air-breathing hypersonic vehicle [J].

Wu, Guanghui ;

Meng, Xiuyun .

AEROSPACE SCIENCE AND TECHNOLOGY, 2016, 54 :174-182

← 1 2 →