摘要
根据模糊系统的结构，构造等价结构的神经网络，针对工程实际应用中模糊控制对于时变参数非线性系统缺乏在线自学习或自调整能力的缺陷，设计了一种增强模糊控制规则自学习能力的模糊神经网络控制器．仿真研究和模拟实验证明了方法的可行性．
Fuzzy control is a human-imitating control technique, which is independent ofmathematical model of plants. It utilizes priori knowledge to carry out approximatereasoning. But it is lack of the ability of self-tuning or self-learning in industrialapplications. The temperature control process of industrial Process is a multivariable andnonlinear dynamic system. To cater for the practical requirements, this paper presents afuzzy network control strategy which is able to enhance the capacity of self-learning offuzzy control rules, based on the self-leaning ability of neural networks. Simulationresearch and physical analog experiment prove the feasibility of this control strategy.
出处
《北京工业大学学报》
CAS
CSCD
1999年第2期97-102,共6页
Journal of Beijing University of Technology
基金
北京市教委科学研究及发展
