Fuzzy Neural Pseudo Control With Prescribed Performance for Waverider Vehicles: A Fragility-Avoidance Approach

A fuzzy-neural-approximation-based pseudo nonaffine control protocol is proposed for waverider vehicles (WVs), which is capable of guaranteeing tracking errors with desired prescribed performance and rejecting the obstacle of fragility inherent to the traditional prescribed performance control (PPC)...

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Published in:	IEEE transactions on cybernetics Vol. 53; no. 8; pp. 4986 - 4999
Main Authors:	Bu, Xiangwei, Lv, Maolong, Lei, Humin, Cao, Jinde
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Aerodynamics Artificial neural networks Fragility Fuzzy control Fuzzy logic nonaffine dynamics prescribed performance Protocols pseudo control Robustness Tracking Tracking errors Transient analysis Uncertainty Vehicle dynamics waverider vehicles (WVs)
ISSN:	2168-2267, 2168-2275, 2168-2275
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Abstract	A fuzzy-neural-approximation-based pseudo nonaffine control protocol is proposed for waverider vehicles (WVs), which is capable of guaranteeing tracking errors with desired prescribed performance and rejecting the obstacle of fragility inherent to the traditional prescribed performance control (PPC). The pseudo control is defined to approximate the nonaffine dynamics of WVs, while there is no need of model affinization. Furthermore, fuzzy neural approximators are combined with the adaptive compensation strategy to resist both system uncertainties and external disturbances. Especially, a new type of nonfragile prescribed performance, being able to self-adjust its prescribed funnel, is proposed to remedy the fragility defect associated with the existing PPC. Finally, the realizability of the spurred prescribed performance is proved via stability proof, and the superiority of the addressed design is tested by compared simulations.
AbstractList	A fuzzy-neural-approximation-based pseudo nonaffine control protocol is proposed for waverider vehicles (WVs), which is capable of guaranteeing tracking errors with desired prescribed performance and rejecting the obstacle of fragility inherent to the traditional prescribed performance control (PPC). The pseudo control is defined to approximate the nonaffine dynamics of WVs, while there is no need of model affinization. Furthermore, fuzzy neural approximators are combined with the adaptive compensation strategy to resist both system uncertainties and external disturbances. Especially, a new type of nonfragile prescribed performance, being able to self-adjust its prescribed funnel, is proposed to remedy the fragility defect associated with the existing PPC. Finally, the realizability of the spurred prescribed performance is proved via stability proof, and the superiority of the addressed design is tested by compared simulations. A fuzzy-neural-approximation-based pseudo nonaffine control protocol is proposed for waverider vehicles (WVs), which is capable of guaranteeing tracking errors with desired prescribed performance and rejecting the obstacle of fragility inherent to the traditional prescribed performance control (PPC). The pseudo control is defined to approximate the nonaffine dynamics of WVs, while there is no need of model affinization. Furthermore, fuzzy neural approximators are combined with the adaptive compensation strategy to resist both system uncertainties and external disturbances. Especially, a new type of nonfragile prescribed performance, being able to self-adjust its prescribed funnel, is proposed to remedy the fragility defect associated with the existing PPC. Finally, the realizability of the spurred prescribed performance is proved via stability proof, and the superiority of the addressed design is tested by compared simulations.A fuzzy-neural-approximation-based pseudo nonaffine control protocol is proposed for waverider vehicles (WVs), which is capable of guaranteeing tracking errors with desired prescribed performance and rejecting the obstacle of fragility inherent to the traditional prescribed performance control (PPC). The pseudo control is defined to approximate the nonaffine dynamics of WVs, while there is no need of model affinization. Furthermore, fuzzy neural approximators are combined with the adaptive compensation strategy to resist both system uncertainties and external disturbances. Especially, a new type of nonfragile prescribed performance, being able to self-adjust its prescribed funnel, is proposed to remedy the fragility defect associated with the existing PPC. Finally, the realizability of the spurred prescribed performance is proved via stability proof, and the superiority of the addressed design is tested by compared simulations.
Author	Cao, Jinde Lei, Humin Bu, Xiangwei Lv, Maolong
Author_xml	– sequence: 1 givenname: Xiangwei orcidid: 0000-0001-5783-6659 surname: Bu fullname: Bu, Xiangwei email: buxiangwei1987@126.com organization: Air and Missile Defense College, Air Force Engineering University, Xi'an, China – sequence: 2 givenname: Maolong orcidid: 0000-0001-6406-2399 surname: Lv fullname: Lv, Maolong email: hmleinet@126.com organization: College of Air Traffic Control and Navigation, Air Force Engineering University, Xi'an, China – sequence: 3 givenname: Humin surname: Lei fullname: Lei, Humin email: maolonglv@163.com organization: Air and Missile Defense College, Air Force Engineering University, Xi'an, China – sequence: 4 givenname: Jinde orcidid: 0000-0003-3133-7119 surname: Cao fullname: Cao, Jinde email: jdcao@seu.edu.cn organization: School of Mathematics, Southeast University, Nanjing, China
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SubjectTerms	Aerodynamics Artificial neural networks Fragility Fuzzy control Fuzzy logic nonaffine dynamics prescribed performance Protocols pseudo control Robustness Tracking Tracking errors Transient analysis Uncertainty Vehicle dynamics waverider vehicles (WVs)
Title	Fuzzy Neural Pseudo Control With Prescribed Performance for Waverider Vehicles: A Fragility-Avoidance Approach
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