Abstract
A complete nonlinear framework for the modelling and robust control of nonlinear systems is proposed. The use of neural networks for continuous time modelling to obtain a certain nonlinear canonical form is investigated. The model obtained is used with recently proposed dynamic sliding mode controller design methods. The robustness bounds needed for controller design are determined from modelling errors. A modified version of the backpropagation theorem is also introduced.
| Original language | English |
|---|---|
| Pages (from-to) | 397-423 |
| Number of pages | 27 |
| Journal | International Journal of Robust and Nonlinear Control |
| Volume | 9 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jun 1999 |
| Externally published | Yes |
ASJC Scopus subject areas
- Control and Systems Engineering
- General Chemical Engineering
- Biomedical Engineering
- Aerospace Engineering
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering
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