Research Of Prediction And Control For Chaos Phenomena

Chaos is an analogously unruly and stochastic phenomena appearing in certain system, is especial motorial form of unlinear dynamic system.Chaos phenomena would bring uncertainty to system and make system unstable because of inner randomicity and sensitivity for the original values.So the researches of chaos have greatly theoretical and practical engineering value.So the chaos identification,chaos time series prediction and chaos control were analyzed and researched in this thesis.The main research work is as follows:First,the chaos was identified for the real time series of system.The improved C-C method for reconstructing phase space and the extended small data sets method for computing the largest Lyapunov exponent of system were proposed.Then the improved C-C method was used to reconstruct phase space for the real time series of typic chaos systems—Lorenz system and Hénon system.And the extended small data sets method was used to compute the largest Lyapunov exponents of the reconstructed phase space.Last the results compared with the results of traditionary methods.The compared results showed that the reconstructed phase space using the improved C-C method could present the characteristic of the original system,and the largest Lyapunov exponent of the reconstructed phase space is stable and approaching the real value.Second,the chaos time series was predicted.Using BP neural network and RBF neural network to approach chaos system for modeling prediction models were proposed.And the prediction models were used to predict the real time series of the typic chaos systems—Lorenz system and Logistic mapping,last the prediction results were analysed. The analysed result showed that chaos system is predictable for short time and unpredictable for long time,and these are consistent with theory.Last,the chaos was controlled.The fuzzy neural network controller was designed,and made up of the Logistic mapping control system.The unstable motionless point and 2-periodic orbits of the Logistic mapping were controlled targets for chaos system control simulation experiment,and the controlled results were analyzed.The analyzed results showed that the fuzzy neural network chaos control system would get the prospective controlled purpose.And the cotrolled effect was greatly ideal.