Low-cost adaptive fuzzy neural prescribed performance control of strict-feedback systems considering full-state and input constraints

Low-cost adaptive fuzzy neural prescribed performance control of strict-feedback systems considering full-state and input constraints

A low-cost adaptive neural prescribed performance control (LAFN-PPC) scheme of strict-feedback systems considering asymmetric full-state and input constraints is developed in this paper. In the controller design procedure, one-to-one nonlinear transformation technique is employed to handle the full-...

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Bibliographic Details
Main Authors: Yankui Song, Bingzao Ge, Yu Xia, Shouan Chen, Cheng Wang, Cong Zhou
Format: Article
Language:English
Published: AIMS Press 2022-02-01
Series:AIMS Mathematics
Subjects:
adaptive control
prescribed performance
command filter
full-state constraints
input constraint
low-cost
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2022461?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/math.2022461?viewType=HTML

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