Decentralized adaptive neural control for interconnected stochastic nonlinear delay-time systems with asymmetric saturation actuators and output constraints

作者：Si, Wenjie^*; Dong, Xunde; Yang, Feifei

来源：Journal of the Franklin Institute, 2018, 355(1): 54-80.

DOI：10.1016/j.jfranklin.2017.11.002

• NONSTRICT-FEEDBACK-SYSTEMS
• BARRIER LYAPUNOV FUNCTIONS
• TRACKING CONTROL
• FUZZY CONTROL
• DEAD ZONE
• INPUT
• STABILIZATION
• DESIGN

This paper investigates the problem of decentralized adaptive backstepping control for a class of large-scale stochastic nonlinear time-delay systems with asymmetric saturation actuators and output constraints. Firstly, the Gaussian error function is employed to represent a continuous differentiable asymmetric saturation nonlinearity, and barrier Lyapunov functions are designed to ensure that the output parameters are restricted. Secondly, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions, and the neural networks are employed to approximate the unknown nonlinearities. At last, based on Lyapunov stability theory, a decentralized adaptive neural control method is proposed, and the designed controller decreases the number of learning parameters. It is shown that the designed controller can ensure that all the closed-loop signals are 4-Moment (or 2 Moment) semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of the origin. Two examples are provided to show the effectiveness of the proposed method.

• 出版日期2018-1
• 单位华南理工大学