摘要
本文针对多变量非线性系统 ,提出了一种参数自调整的模糊加权信息融合方法 .利用模糊组合变量降低模糊控制系统的维数 ,根据不同的模糊组合变量对最后决策的作用大小 ,赋予不同的权重来实现对多变量非线性系统的控制 ,在利用反向传播算法对量化系数和加权系数进行自学习后 ,在线进行基于模糊规则的参数自调整 ,有效地解决了多变量模糊控制系统中难于设计多维规则库和在线实现自适应模糊控制的问题 .本文还对所提出的方法进行了仿真实验和实际系统的实验 。
A parameter self-adjusting fuzzy weighted controller of multivariable nonlinear system is designed in this paper. First we use fuzzy composed variables to decrease the fuzzy control system dimensions. Then according to the fuzzy composed variable effect on the final decision, we give each fuzzy composed variable a different weight. After self-learning of quantized parameters and weighted parameters with back propagation algorithm, a real-time parameter self-adjusting method based on fuzzy inference system is presented. It gives a solution to the problem for design and on-line realization of high dimension fuzzy adaptive controller. Simulations and real system experiments show its validity.
出处
《信息与控制》
CSCD
北大核心
2001年第2期135-138,共4页
Information and Control
基金
国家自然科学基金资助课题! (基金编号 :69875 0 0 3 )
