摘要
针对难以建立精确数学模型的复杂过程 ,提出一种基于过程输入输出数据变化关系的模糊建模方法。首先按过程输出随输入变量变化的程度对输入变量论域进行划分 ,在此基础上确定模糊模型的规则总数和前件参数 ;然后根据所建模糊模型可表示为一个前馈模糊神经网络 ,利用 BP学习算法求得过程模糊模型的后件参数。仿真例子验证了该模糊建模方法的有效性 ,同时表明所建模糊规则模型具有较好的泛化能力。
A fuzzy modeling method based on the change relationship between process input and output data is presented for complex processes which are difficult to be mathematically modeled. The domain of discourse of input variables is divided firstly according to the changing degree of the process output while the input variables change. Then based on the dividing the total number and the premise parameters of the fuzzy rules are determined. The BP algorithm is applied to obtain the consequent parameters of the fuzzy rules. The effectiveness of the presented fuzzy modeling method and the generalization ability of the fuzzy rules model are demonstrated by a simulation example.
出处
《控制与决策》
EI
CSCD
北大核心
2001年第3期273-276,共4页
Control and Decision
