Synchronization of a class of partially unknown chaotic systems with integral observer

An integral observer with a compensator based on orthogonal neural networks is proposed for a class of chaotic systems when the output of the system is perturbed and the nonlinear portion of the system is unknown. The designed method achieves chaos synchronization using integral observer theory and the nonlinear approximation ability of the orthogonal neural networks based on the linear portion of chaotic system can be copied. According to Lyapunov stability theory and Linear Matrix Inequality (LMI) technique, the update laws of the network weight and the controller are obtained, and the sufficient criterion of the gain matrix which can be transformed into solving LMI using Schur complements is got. Theoretical analysis and numerical example show the effectiveness of the proposed method.