Adaptive Neural Control for a Class of Low-triangular-structured Nonlinear Systems with H-∞ Performance Analysis

摘要

In this paper,a neural-network-based variable structure control scheme is presented for a class of nonlinear systems with a general low triangular structure.The proposed variable structure controller is proved to be C1,thus can be applied for backstepping design,which has extended the scope of previous nonlinear systems in the form of strict-feedback and pure-feedback.With the help of neural network approximator,H-∞ performance analysis of stability is given.The effectiveness of proposed control law is verified via simulation.