Abstract
This paper presents a Lyapunov function based neural network tracking control strategy for single-input-single-output nonlinear dynamic systems. The proposed architecture is composed of two feed-forward neural networks operating as controller and estimator in a unified framework. The network parameters are tuned online with a Lyapunov function based backpropagation learning algorithm. The closed-loop error convergence and stability are analyzed with Lyapunov stability theory. Two simulation case studies are included that successfully validate the proposed controller performance.
Original language | English |
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Title of host publication | Proceedings of the IEEE International Conference on Industrial Technology |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 321-325 |
Number of pages | 5 |
Volume | 2015-June |
Edition | June |
DOIs | |
Publication status | Published - Jun 16 2015 |
Event | 2015 IEEE International Conference on Industrial Technology, ICIT 2015 - Seville, Spain Duration: Mar 17 2015 → Mar 19 2015 |
Other
Other | 2015 IEEE International Conference on Industrial Technology, ICIT 2015 |
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Country | Spain |
City | Seville |
Period | 3/17/15 → 3/19/15 |
Keywords
- direct adaptive inverse control
- indirect adaptive inverse control
- Lyapunov function
- neural inverse tracking
- stable adaptive tracking
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Computer Science Applications