Stability of A Class of RNN Controllers for First-order Uncertain Systems

This paper studies the stability of a class of first-order uncertain systems controlled by a simple recurrent neural network (RNN) controller. The convergence conditions are given. The relationship between the parameters of RNN controller and its robustness is quantitatively analyzed for the linear uncertain system. Simulation examples are provided to verify the analysis results.