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Fuzzy Control System of Hydraulic Roll Bending Based on Genetic Neural Network 被引量:2
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作者 JIAChun-yu LIUHong-min ZHOUHui-feng 《Journal of Iron and Steel Research(International)》 SCIE CAS CSCD 2005年第3期22-27,共6页
For nonlinear hydraulic roll bending control, a new fuzzy intelligent control method was proposed based on the genetic neural network. The method taking account of dynamic and static characteristics of control system ... For nonlinear hydraulic roll bending control, a new fuzzy intelligent control method was proposed based on the genetic neural network. The method taking account of dynamic and static characteristics of control system has settled the problems of recognizing and controlling the unknown, uncertain and nonlinear system successfully, and has been applied to hydraulic roll bending control. The simulation results indicate that the system has good performance and strong robustness, and is better than traditional PID and neural-fuzzy control. The method is an effective tool to control roll bending force with increased dynamic response speed of control system and enhanced tracking accuracy. 展开更多
关键词 genetic algorithm neural network fuzzy control hydraulic roll bending SHAPE
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Modeling and Simulation of Hydraulic Roll Bending System Based on CMAC Neural Network and PID Coupling Control Strategy 被引量:3
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作者 JIA Chun-yu SHAN Xiu-ying +2 位作者 CUI Yan-cao BAI Tao CUI Fa-jun 《Journal of Iron and Steel Research(International)》 SCIE EI CAS CSCD 2013年第10期17-22,共6页
The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise m... The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise mathemati- cal model for control. So, a new method for establishing a hydraulic roll bending control system is put forward by cerebellar model articulation controller (CMAC) neural network and proportional-integral-derivative (PID) coupling control strategy. The non-linear relationship between input and output can be achieved by the concept mapping and the actual mapping of CMAC. The simulation results show that, compared with the conventional PID control algo- rithm, the parallel control algorithm can overcome the influence of parameter change of roll bending system on the control performance, thus improve the anti jamming capability of the system greatly, reduce the dependence of con- trol performance on the accuracy of the analytical model, enhance the tracking performance of hydraulic roll bending loop for the hydraulic and roll bending force and increase system response speed. The results indicate that the CMAC-P1D coupling control strategy for hydraulic roll bending system is effective. 展开更多
关键词 hydraulic roll bending CMAC neural network PID control genetic algorithm
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