This paper focuses on the issue of adaptive finite-time attitude tracking control for an autonomous airship subject to full state constraints and uncertainties. A tan-type nonlinear mapping function is designed to convert the constrained system into a new one without constraints, such that the state constraints are never violated. Neural networks are introduced to approximate uncertainties. A \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$C^1$$\end{document} finite-time adaptive control scheme is introduced by employing a smooth switching function. Through stability analyses, all signals are semi-globally uniformly ultimately bounded, and the state constraints are never transgressed. Finally, simulations are implemented to evaluate the efficacy of the developed approach.
Adaptive Finite-Time Attitude Tracking Control of an Autonomous Airship with Full State Constraints and Uncertainties
Lect. Notes Electrical Eng.
2021-10-30
11 pages
Article/Chapter (Book)
Electronic Resource
English
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