摘要
提出了一种基于小波神经网络的自适应控制方法,该方法利用两个小波神经网络作为自适应控制系统的辨识器和控制器来构成自适应控制系统.由于小波函数具有紧支性以及神经网络的非线性映射能力,因而在所构成的控制系统中,辨识器能更准确地近似具有较强非线性被控对象的动态特性,控制器能产生较为复杂的控制规律.仿真结果表明。
Using the wavelet neural networks, an adaptive control system, with two wavelet neural networks as controller and identifier respectively, is developed for a class of nonlinear systems. Because the wavelet neural networks have the ability to approximate nonlinear functions and good advantage of time frequency localization properties, this system can identify nonlinear system dynamic characters more precisely, and can map more complex control strategies. Results show that this control system is more effective than those based on normal neural networks.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2000年第2期75-79,共5页
Journal of Xi'an Jiaotong University
