基于DRNN自適應(yīng)反饋補償控制器設(shè)計與應(yīng)用

在軋鋼控制系統(tǒng)中，由于軋機兩側(cè)液壓壓下系統(tǒng)的不一致會導(dǎo)致帶材橫向厚度差分布
不均勻，直接影響帶材的板形質(zhì)量，針對此問題，本文提出將對角遞歸網(wǎng)絡(luò)自適應(yīng)PID 控制器用于反饋回路中的補償控制方案，用以提高軋機兩側(cè)壓下動態(tài)同步的品質(zhì)。仿真實驗結(jié)果表明，此種方案能滿足被控對象對高精度同步控制的要求。
關(guān)鍵詞：液壓伺服；對角遞歸網(wǎng)絡(luò)；板形控制；遞推預(yù)報誤差算法

Design and application of self-adaptive feedback compensation controller based on
Dynamic Recurrent Neural Network ZHAO Xu ， MENG Xiang-ping (1. Electric and Information Engineer School,Changchun Engineer Uniersity, Changchum，Jilin Province 130012, China ; 2.Electric and Information Engineer School ,Beihua University,Jilin Jilin province ,132021,China) Abstract: The vary character of both side of rolling mill hydraulic pressing system leads to an unequal horizontal thickness difference distribution of strip which affects strip shape directly .In order to resolve this problem, the neural network self-adaptive PID based on Dynamic Recurrent Neural Network was used in feedback circle of rolling mill hydraulic pressing system to improve the synchronization of both side of rolling mill hydraulic pressing system .The results of simulation tests indicate this method can satisfy the demands of the controlled object for the high precision synchronous control.
keywords: Hydraulics servo; Dynamic Recurrent Neural Network; shape control ;recursive prediction error algorithm