Back to Search
Start Over
Adaptive neural network tracking control for uncertain nonlinear systems with input delay and saturation.
- Source :
-
International Journal of Robust & Nonlinear Control . May2020, Vol. 30 Issue 7, p2593-2610. 18p. - Publication Year :
- 2020
-
Abstract
- Summary: In this article, the adaptive tracking control problem is considered for a class of uncertain nonlinear systems with input delay and saturation. To compensate for the effect of the input delay and saturation, a compensation system is designed. Radial basis function neural networks are directly utilized to approximate the unknown nonlinear functions. With the aid of the backstepping method, novel adaptive neural network tracking controllers are developed, which can guarantee all the signals in the closedâloop system are semiglobally uniformly ultimately bounded, and the system output can track the desired signal with a small tracking error. In the end, a simulation example is given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10498923
- Volume :
- 30
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- International Journal of Robust & Nonlinear Control
- Publication Type :
- Academic Journal
- Accession number :
- 142770642
- Full Text :
- https://doi.org/10.1002/rnc.4887