Neural Network-Based Adaptive Dynamic Surface Control for Inverted Pendulum System

摘要

In this paper, a novel neural network (NN)-based adaptive dynamic surface control (DSC) is proposed for inverted pendulum system. This scheme overcomes the problem of "explosion of complexity" which is inherent in the traditional backstepping technique. Meanwhile, the effect of input saturation constrains is considered in the control design. All the signals in the closed-loop system are proved uniformly ultimately bounded. Finally, the experimental platform simulation results are used to demonstrate the effectiveness of the proposed scheme.