Flatness predictive model based on T-S cloud reasoning network implemented by DSP  

作　　者：ZHANG Xiu-ling GAO Wu-yang LAI Yong-jin CHENG Yan-tao 张秀玲;高武杨;来永进;程艳涛

机构地区：[1]Key Laboratory of Industrial Computer Control Engineering of Hebei Province,Yanshan University,Qinhuangdao 066004,China [2]National Engineering Research Center for Equipment and Technology of Cold Strip Rolling,Yanshan University,Qinhuangdao 066004,China

出　　处：《Journal of Central South University》2017年第10期2222-2230,共9页中南大学学报（英文版）

基　　金：Project(E2015203354)supported by Natural Science Foundation of Steel United Research Fund of Hebei Province,China;Project(ZD2016100)supported by the Science and the Technology Research Key Project of High School of Hebei Province,China;Project(LJRC013)supported by the University Innovation Team of Hebei Province Leading Talent Cultivation,China;Project(16LGY015)supported by the Basic Research Special Breeding of Yanshan University,China

摘　　要：The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.

关 键 词：T-S CLOUD reasoning neural NETWORK CLOUD MODEL FLATNESS predictive MODEL hardware implementation digital signal PROCESSOR genetic ALGORITHM and simulated annealing ALGORITHM (GA-SA) 

分 类 号：TG142.1[一般工业技术—材料科学与工程] TP18[金属学及工艺—金属材料]