Improved adaptive control for wing rock via fuzzy neural network with randomly assigned fuzzy membership function parameters
文献类型：期刊论文
| 作者 | Rong, Hai-Jun1; Han, Sai2; Bai, Jian-Ming3; Liang, Yong-Qi1 |
| 刊名 | aerospace science and technology
 |
| 出版日期 | 2014-12-01 |
| 卷号 | 39页码:614-627 |
| 关键词 | Wing rock Fuzzy neural network Online sequential fuzzy extreme learning machine Adaptive control |
| ISSN号 | 1270-9638 |
| 产权排序 | 3 |
| 合作状况 | 国内 |
| 英文摘要 | two stable adaptive fuzzy-neural control schemes within the indirect and direct frameworks are proposed to suppress the wing rock occurring at high angles of attack. in the two control strategies, a fuzzy neural network (fnn) with any bounded nonconstant piecewise continuous membership function is used to approximate the system nonlinear dynamics and external disturbances. differently from the existing techniques, the parameters of the fuzzy membership functions are determined based on the recently developed fuzzy-neural algorithm named online sequential fuzzy extreme learning machine (os-fuzzy-elm) where the fuzzy membership function parameters need not be adjusted and could randomly be generated according to any given continuous probability distribution without any prior knowledge. this simplifies the design of the controllers. furthermore to ensure stable control performance, the tuning laws of the consequent parameters are derived using the projection algorithm and lyapunov stability theorem. the merits of the proposed control schemes lie in the simplicity, robustness and stability, which manifests they can be applied for online learning and real-time control. in order to evaluate the performance of the proposed two control schemes, a comparison between a neural control, a fuzzy control and a fuzzy-neural control is carried out on various initial conditions. results indicate the performance of the proposed controllers is superior using the randomly assigned fuzzy membership function parameters. (c) 2014 elsevier masson sas. all rights reserved. |
| WOS标题词 | science & technology ; technology |
| 类目[WOS] | engineering, aerospace |
| 研究领域[WOS] | engineering |
| 关键词[WOS] | slender delta-wings ; hypersonic flight vehicle ; extreme learning-machine ; systems ; approximation ; design ; motion ; model |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000347743100063 |
| 公开日期 | 2015-03-19 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/22413]  |
| 专题 | 西安光学精密机械研究所_光学定向与测量技术研究室 |
| 作者单位 | 1.Xi An Jiao Tong Univ, Sch Aerosp, State Key Lab Strength & Vibrat Mech Struct, Xian 710049, Shaanxi, Peoples R China 2.AVIC Xian Aircraft Branch Co, Inst Avion & Flight Control, Yanliang 710089, Shaanxi, Peoples R China 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Opt Direct & Pointing Tech Res Dept, Xian 710119, Shaanxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Rong, Hai-Jun,Han, Sai,Bai, Jian-Ming,et al. Improved adaptive control for wing rock via fuzzy neural network with randomly assigned fuzzy membership function parameters[J]. aerospace science and technology,2014,39:614-627. |
| APA | Rong, Hai-Jun,Han, Sai,Bai, Jian-Ming,&Liang, Yong-Qi.(2014).Improved adaptive control for wing rock via fuzzy neural network with randomly assigned fuzzy membership function parameters.aerospace science and technology,39,614-627. |
| MLA | Rong, Hai-Jun,et al."Improved adaptive control for wing rock via fuzzy neural network with randomly assigned fuzzy membership function parameters".aerospace science and technology 39(2014):614-627. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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