Adaptive Neuro-Genetic Control of Chaos applied to the Attitude Control Problem

Dracopoulos, D. and Jones, A.J. 1997. Adaptive Neuro-Genetic Control of Chaos applied to the Attitude Control Problem. Neural Computing & Applications. 6 (2), pp. 102-115. https://doi.org/10.1007/BF01414007

TitleAdaptive Neuro-Genetic Control of Chaos applied to the Attitude Control Problem
AuthorsDracopoulos, D. and Jones, A.J.
Abstract

Conventional adaptive control techniques have, for the most part, been based on methods for linear or weakly non-linear systems. More recently, neural network and genetic algorithm controllers have started to be applied to complex, non-linear dynamic systems. The control of chaotic dynamic systems poses a series of especially challenging problems. In this paper, an adaptive control architecture using neural networks and genetic algorithms is applied to a complex, highly nonlinear, chaotic dynamic system: the adaptive attitude control problem (for a satellite), in the presence of large, external forces (which left to themselves led the system into a chaotic motion). In contrast to the OGY method, which uses small control adjustments to stabilize a chaotic system in an otherwise unstable but natural periodic orbit of the system, the neuro-genetic controller may use large control adjustments and proves capable of effectively attaining any specified system state, with no a prioriknowledge of the dynamics, even in the presence of significant noise.

JournalNeural Computing & Applications
Journal citation6 (2), pp. 102-115
ISSN0941-0643
Year1997
PublisherSpringer
Digital Object Identifier (DOI)https://doi.org/10.1007/BF01414007
Publication dates
PublishedJun 1997

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