Stability Analysis for a Two-Time-Scale Neural Tracking Controller

The stability of a two-time scale neural tracking controller is analyzed using Lyapunov stability theory. The results show that the tracking error of the system is uniformly bounded and converges to a bounded region if the two-time-scale neural tracking controller is used. Moreover, the region depends only on the accuracy of the slow learning rule is a switching leakage term is used in the fast learning rule.<>