Control systems in modern automatic engineering are nonlinear , time - changed and indefinite . lt is difficult to model by traditional method , even sometime impossible . under these circumstances we should apply model identification to gain the approximate model of object for effective control , there are many models to be chosen , fuzzy model is one of them , it is put forward with the development of fuzzy control . fuzzy model has characteristics of general approximation and strong nonlinear , it is fit for describing complex , nonlinear systems . to avoid rules expansion when the number of input values are very big . in this paper we apply hierarchical fuzzy model to resolve this problem , we also illustrate it has general approximation to any nonlinear systems . genetic algorithm is a algorithm to help find the best parameters of process . lt has abilities of global optimizing and implicit parallel , it can be generally used for all applications . in our paper we use fuzzy model as predictive model and apply ga to identify fuzzy model ( including hierarchical fuzzy model ) , we made experiments to nonlinear predictive systems and got very good results . the paper contains chapters as below : chapter 1 preface 現(xiàn)代控制工程中的系統(tǒng)多表現(xiàn)為非線性、時(shí)變和不確定性,采用傳統(tǒng)的建模方法比較困難,或者根本無(wú)法實(shí)現(xiàn),在這種情況下,要實(shí)現(xiàn)有效的控制,必須采用模型辨識(shí)的方法來(lái)獲取對(duì)象的近似模型,并加以控制,目前用于系統(tǒng)辨識(shí)的模型種類很多,模糊模型是其中的一種,它隨著模糊控制的發(fā)展而被人提出,模糊模型具有萬(wàn)能逼近和強(qiáng)非線性的特點(diǎn),比較適合于描述復(fù)雜非線性系統(tǒng),為了解決模糊模型在輸入變量較多時(shí)規(guī)則數(shù)膨脹的問(wèn)題,文中引入遞階型模糊模型,并引證這種結(jié)構(gòu)的通用逼近特性。遺傳算法是模擬自然界生物進(jìn)化“優(yōu)勝劣汰”原理的一種參數(shù)尋優(yōu)算法,它具有隱含并行性和全局最優(yōu)化的能力,并且對(duì)尋優(yōu)對(duì)象的要求比較低,在工程應(yīng)用和科學(xué)研究中,得到了廣泛的應(yīng)用,本文將遺傳算法引入模糊模型的辨識(shí),取得了很好的效果。