Fixed-weight controller for multiple systems
- 22 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 773-778
- https://doi.org/10.1109/icnn.1997.616120
Abstract
We demonstrate here a perhaps unexpected result: the ability of a single fixed-weight time-lagged recurrent network, properly trained, to act as a stabilizing controller for multiple (here 3) distinct and unrelated systems, without explicit knowledge of system identity. This capability, which may be regarded as a challenge to the usual understanding of what constitutes an adaptive system, seemed plausible to us on the basis of our earlier results on both multiple time-series prediction and robust controller training. We describe our training method, which has been enhanced toward enforcing stability of the closed-loop system and dealing with process noise, and provide some results.Keywords
This publication has 6 references indexed in Scilit:
- Adaptation from fixed weight dynamic networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Training of robust neural controllersPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Training controllers for robustness: multi-stream DEKFPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Dynamic neural network methods applied to on-vehicle idle speed controlProceedings of the IEEE, 1996
- Gradient methods for the optimization of dynamical systems containing neural networksIEEE Transactions on Neural Networks, 1991
- Backpropagation through time: what it does and how to do itProceedings of the IEEE, 1990