Low dimensional chaos in elevator peak traffic

• 作 者: LIJun-fang[1]ZONGQun[2]ZHANGJing-long[2]WANGFang[2]
• 机 构: School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China School of
• 出 处: 2011年中国智能自动化会议
• 发表日期: 2011年期

　　Nonlinear time series techniques were applied to
　　analyze up-peak and down-peak traffic flow data and
　　energy
　　consumption data in elevator system. Phase space was
　　reconstructed using the delay embedding theorem,
　　which described the
　　behaviour evolution of a nonlinear system. Embedding
　　parameters including delay time and embedding
　　dimension were estimated
　　using the mutual information of the data and the
　　false nearest neighbour algorithm, respectively. Due
　　to the attractor of the elevator
　　traffic flow data and energy consumption data from
　　reconstruction was not a necessarily sufficient
　　indication of chaos, the correlation
　　dimension and the largest Lyapunov exponent aiming at
　　the above data were calculated. Based on these
　　analysis and calculation, the
　　results indicate that low dimensional chaotic
　　characteristics obviously exist in the up-peak and
　　down-peak traffic flow data and
　　energy consumption data. The result helps to adjust
　　the group control scheduling methods according to the
　　chaotic behaviour of the
　　peak flow and the building energy consuming to
　　increase the performance index of the system.