Prescribed performance synchronization for uncertain chaotic systems with input saturation based on neural networks

In this paper, a prescribed performance adaptive neural network synchronization is investigated for a class of unknown chaotic systems in the presence of input saturation and external unknown disturbances. A prescribed performance function is employed to transform the constraint problem of chaotic synchronization control error into the problem of guaranteeing the boundedness of the transformed error. By introducing the Gaussian error function, the input saturation is handled. A neural network-based synchronization control scheme is then developed. Under the developed synchronization control scheme, the synchronization of uncertain chaotic systems is achieved with different initial conditions. Numerical simulation results further demonstrate the effectiveness of the proposed synchronization control scheme for unknown chaotic systems subject to external unknown disturbances and input saturation.