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作 者:JIA Chun-yu WANG Ying-rui ZHOU Hui-feng
出 处:《Journal of Iron and Steel Research International》2004年第6期25-29,共5页
摘 要:Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward,and a self-organizing fuzzy control model was established.The structure of the network can be optimized dynamically.In the course of studying,the network can automatically adjust its structure based on the specific questions and make its structure the optimal.The input and output of the network are fuzzy sets,and the trained network can complete the composite relation,the fuzzy inference.For decreasing the off-line training time of BP network,the fuzzy sets are encoded.The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward,and a self-organizing fuzzy control model was established.The structure of the network can be optimized dynamically.In the course of studying,the network can automatically adjust its structure based on the specific questions and make its structure the optimal.The input and output of the network are fuzzy sets,and the trained network can complete the composite relation,the fuzzy inference.For decreasing the off-line training time of BP network,the fuzzy sets are encoded.The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.
关 键 词:dynamic BP network self-organizing fuzzy control encode DC mill thickness SHAPE synthetical adjustment
分 类 号:TG334.9[金属学及工艺—金属压力加工]
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