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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Bibliographic Details
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
Online Access:Get full text
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Summary: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.
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ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2023.3255925