The temperature system identification of the PVC stripper tower top based on PSO-FCM optimized T-S model
In view of the characteristics of T-S model, such as easily expressing complex dynamic systems and the characteristics of PSO algorithm which could find the optimal solution of complex problems easily. This paper will presents a new identification method based on the T-S model in which FCM parameters is optimized by PSO.The mathematical model of the temperature system of the PVC stripper tower top will be built by this method . First, an adaptive number of clusters of C-means clustering fuzzy (FCM) algorithm is used to find the appropriate number of clusters in FCM, and both the number of fuzzy rules and the premise parameters of the model can are determined. Using PSO algorithm to optimize the FCM algorithm, then getting the best membership matrix by the FCM algorithm based on PSO in the end.Then,a least square algorithm is applied to determine the parameters of consequent part of T-S model. The simulation result shows the effectiveness and feasibility of the modeling method.
T-S model fuzzy c-means clustering (FCM) least squares algorithm polyvinyl chloride (PVC) Particle swarm optimization algorithm(PSO)
Gao Shuzhi Dou Xing Gao Xianwen
College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, Chi College of Information Science and Engineering, Northeastern University, Shenyang 110189, China
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
2541-2544
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）