基于BP 神經(jīng)網(wǎng)絡(luò)能以任意精度逼近任何非線性連續(xù)函數(shù)的原理。通過(guò)在MATLAB
環(huán)境下，對(duì)典型的不穩(wěn)定、非線性、強(qiáng)耦合的倒立擺系統(tǒng)建立了BP 神經(jīng)網(wǎng)絡(luò)辨識(shí)結(jié)構(gòu)，并對(duì)辨識(shí)結(jié)果進(jìn)行了分析。結(jié)果表明BP 神經(jīng)網(wǎng)絡(luò)對(duì)非線性倒立擺模型的辨識(shí)是有效的。
關(guān)鍵詞：BP 神經(jīng)網(wǎng)絡(luò)；倒立擺 ；系統(tǒng)辨識(shí)
BP Neural Network for Non-linear Inverted Pendulum System Identification YAN xin ，ZHAO ying kai，DOU dong yang (College of Automation,NanJing Univ. of Technology，JiangSu 210009 ,China) Abstract:Base on the theory that the BP neural network can compel any non-linear function by any precision. Under the circumstance of MATLAB, the neural network structure identification of a typical unstable, non-linear and strong coupling inverted pendulum system is established. Analyze of the result of identification prove that it is effective for neural network to identify the non-linear inverted pendulum system.
Key words: BP Neural Network ；Inverted Pendulum；System Identification