Research Of Chaos Synchronization Based On Particle Swarm Optimiziton And Adaptive Inverse Control

In recent years, chaos are widely studied and applied in secure communication and other fields , because of its characters of sensitive to initial conditions, similar to noise and continuous, wide-band frequency spectrum. However, the theory of chaotic control and synchronization is still very unripe presently, and until now there are a lot of problems on theory and technology unsolved. Considering some problems existing in the studies of chaotic synchronization at present , the problems of chaotic synchronization on theory, approaches and application, etc are discussed in this paper, with the continuous and discrete chaotic systems as the objects. The main purpose is to provide theory approaches and expand theory foundation for chaotic synchronization and its application.Firstly, considering particle swarm optimization (PSO) algorithm has the disadvantage of easy getting into premature trap, the modified particle swarm optimization (MPSO) algorithm and bee evolution modifying particle swarm optimization (BEMPSO) algorithm were given in this paper. Five typical testing functions is used to analyze and test it using the different particle swarm optimization algorithm . The results are analysed and contrasted , BEMPSO has very good convergence. It also lays an effective theoretical foundation for the studies of chaotic system synchronization in the latter chapters.Secondly, using delamination delivery bee evolution modifying particle swarm optimization (DDBEMPSO) algorithm train artificial neural network for modeling continuous and discrete chaotic systems. Then gives training algorithms of DDBEMPSO based on RBFNN and based on CNN. Through the continuous and discrete chaotic mapping simulation , the simulating results indicates the improved method can impove search efficiency , prevent premature and realize global optimization effectively.Thirdly, in allusion to chaos asynchronization issues caused by channel noise infuenceing chaos signal, design an adaptive inverse controller to cancel disturbance and noise in chaos synchronization system according to the adaptive inverse theory. Adaptive inverse control canceling noise in signals has optimality , it is very much suitable for the application in chaos synchronization . The continuous and discrete chaotic systems synchronization disturbed by noises is investigated using this method. By the comparative digital simulation using of DDBEMPSO algorithm optimizing RBFNN and CNN to identify and control discrete chaotic systems synchronization, it concludes that the latter is better.Finally, the synchronization approaches above are applied in secure communication by amplitude masking modulation and the general procedures of discrete chaotic systems synchronization controlled adaptive inverse by amplitude masking modulation is discribed. Study of simulation is carried out by using Logistic mapping and Lorenz chaos system as example . It mainly interprets hyperchaotic synchronization secure communication and analyses 4-dimensional hyperchaotic LC oscillator model , using DDBEMPSO algorithm optimizes artificial neural network , identifies object model and have adaptive filtering in controller and disturbance canceller . Through sumulation of hyperchaotic synchronization secure communication by amplitude masking modulation , the simulation result shows the synchronization system accomplish the signal secure communication transmission truly.