摘要
在文献[1]的基础上,引入模糊神经网络和参数自调整算法,改善系统的智能,使系统具有自学习和自调整模糊规则的能力.仿真结果表明,该方法能实现静态解耦,并提高了系统的抗干扰能力和鲁棒性,改善了系统的性能.
The paper uses fuzzy neural network and self-adjusting parameter algorithm based on article[1] to enhance the system intelligent and ability of self-learning and self-adjusting fuzzy rules. Simulation resuits show the system can realize static decoupling and increase the ability of resisting disturbance and robustness and enhance its performance.
出处
《湖南工程学院学报（自然科学版）》
2008年第3期5-9,共5页
Journal of Hunan Institute of Engineering(Natural Science Edition)
基金
湖南省自然科学基金资助项目(01JJY2062)
关键词
解耦控制
模糊神经网络
多变量系统
decoupling control
fuzzy neural network
multivariable system
