Abstract
In this paper, an adaptive neural network (NN) synchronization controller is designed for two identical strict-feedback chaotic systems (SFCSs) subject to dead-zone input. The dead-zone models together with the system uncertainties are approximated by NNs. The dynamic surface control (DSC) approach is applied in the synchronization controller design, and the traditional problem of “explosion of complexity” that usually occurs in the backstepping design can be avoided. The proposed synchronization method guarantees the synchronization errors tend to an arbitrarily small region. Finally, this paper presents two simulation examples to confirm the effectiveness and the robustness of the proposed control method.
Highlights
Chaos synchronization (CS) has been widely investigated based on the results of [1]
Yu and Cao [20] addressed the synchronization of chaotic systems with time delay
The other is that the control of strict-feedback chaotic systems (SFCSs) subject to dead-zone input has been rarely investigated
Summary
Chaos synchronization (CS) has been widely investigated based on the results of [1]. A lot of works have been given on this theme because of its possible application in many fields such as communications, information processing [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]. The other is that the control of strict-feedback chaotic systems (SFCSs) subject to dead-zone input has been rarely investigated. This paper will propose the synchronization control methods for a class of uncertain SFCSs with dead-zone input and disturbances. R control input and the output of the dead zone, dk(t) denotes an unknown external disturbance satisfying |dk(t)| ≤ dk∗, where dk∗ is a positive constant. If the virtual signal is given as (22) and (23), the control law is chosen as (32), the adaptive law is given as (34), all signals are uniformly bounded, and the synchronization error remains in an arbitrarily small region of zero.
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