Title :
Controlling chaos with an artificial neural network
Author :
Otawara, K. ; Fan, L.T.
Author_Institution :
Dept. of Chem. Eng., Kansas State Univ., Manhattan, KS, USA
Abstract :
A novel method for controlling chaos is proposed by resorting to an artificial neural network (ANN). It is widely applicable where the behavior of a chaotic system is well described by the next return map. The method appears to be superior to other alternatives since a single ANN trained with time-series data is capable of controlling chaos, i.e., rendering stable multiple unstable periodic orbits embedding a strange attractor, and extensive computation or analysis is unnecessary. Its efficacy is illustrated with an example of a logistic map
Keywords :
chaos; neural nets; neurocontrollers; nonlinear dynamical systems; chaos control; chaotic system; logistic map; neural network; next return map; strange attractor; time-series data; unstable periodic orbits; Artificial neural networks; Chaos; Chemical engineering; Embedded computing; Logistics; Motion control; Nonlinear systems; Orbits; Time series analysis; Trajectory;
Conference_Titel :
Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
Conference_Location :
Yokohama
Print_ISBN :
0-7803-2461-7
DOI :
10.1109/FUZZY.1995.409945