Abstract: In this paper，a direct adaptive neural network controller is proposed arming at the unknown functions and uncertain disturbance of a class of nonlinear systems.The Radial Basis Function （RBF） neural network is used as approximation model for the unknown functions due to their nicer approximation capabilities，and nonlinear damping terms is used to counteract the disturbances.The proposed method’s advantages are simple structure，brief algorithm，nicer stability and convergence with conditions.Simulation results are presented to verify the effectiveness of the approach.

摘要： 为解决一类带干扰的不确定非线性系统中存在的两类未知项——未知函数和外界干扰，采用了直接自适应神经网络控制方法设计控制器。控制器设计中利用径向基函数神经网络良好的逼近性来近似未知函数，利用非线性衰减项来抑制干扰。所用方法结构简单、算法简洁，在一定条件下稳定性和收敛性能定性地得到保证。最后，仿真结果证明了该方法是正确的。