：针对能够采用仿射非线性表示的含有未建模动态的SISO非线性系统，讨论了一种基于神经网络的自适应

控制方法．该方法对受控对象的已知部分．采用反馈线性化方法设计控制器，用神经网络在线补偿未建模动态及

外部干扰等引起的误差，从而实现自适应控制。对具有未建模动态的双车倒立摆设计了输出反馈自适应控制系

统．仿真表明该方法是有效的。 -A discussion is devoted to design neural network adaptive control scheme of the SISO (single

input and single output)nonlinear system with unmodeled dynamics．According to the known part of

the plant．feedback Iinearization method iS used to design the controller．The error resulted from the un～

modeled dynamics and the external disturbance is compensated by online neural network．The neural

networks are designed as a five layer fuzzy neural network and its construction is optimized by genetic al—

gorithms．It has been used to approtimate the nonlinear function of system and to compesate the error of

unmodeled dynamic．The design of neural network adaptive controller has better performances．The

method is verified by the digital simulation of tWO—·cart with inverted·-pendulum system and unmodeled

dynamics．