Adaptive neural network tracking design for a class of uncertain nonlinear discrete-time systems with dead-zone

作者：Liu YanJun^*; Liu Lei; Tong ShaoCheng

来源：Science China Information Sciences, 2014, 57(3): 032206.

DOI：10.1007/s11432-012-4779-0

• adaptive control
• RBF neural network
• non-symmetric dead-zone
• backstepping design
• uncertain nonlinear systems

In this paper, the stability and control issues of a class of uncertain nonlinear discrete-time systems in the strict feedback form are investigated. The dead-zone input in the systems, whose property is non-symmetric and discretized, is investigated. The unknown functions in the systems are approximated by using the radial basis function neural networks (RBFNNs). Backstepping design procedure is employed in the controller and the adaptation laws design. Lyapunov analysis method is utilized to prove the stability of the closed-loop system. A simulation example is given to illustrate the effectiveness of the proposed approach.

• 出版日期2014-3
• 单位辽宁工业大学