Fixed-weight controller for multiple systems
L.A. Feldkamp, G.V. Puskorius · Proceedings of International Conference on Neural Networks (ICNN'97) · 2002
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.