Abstract
The limitations of the adaptive control techniques that have been described so far, the first encouraging results on simple control problems using neural networks reported in the literature [7, 17, 141], the possibility of hardware implementation of artificial neural networks, and the current desire for reconfigurable flight control are the main motivations for the work described here.
Instead of chasing after the beasts, which would have accomplished little or nothing, Klapaucius, a true theoretician, approached the problem methodically; in squares and promenades, in barns and hostels he placed probabilistic battery-run dragon dampers, and in no time at all the beasts were extremely rare.
Stanislaw Lem
(The Cyberiad)
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© 1997 Springer-Verlag London
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Dracopoulos, D.C. (1997). Adaptive Control Architecture. In: Evolutionary Learning Algorithms for Neural Adaptive Control. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0903-7_8
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DOI: https://doi.org/10.1007/978-1-4471-0903-7_8
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