Systems Identification of Hammerstein nonlinear Systems for Dual-rate Sampling and Output Signal Quantized
To the Hammerstein nonlinear systems with dual-rate sampling and output signal quantization, an auxiliary model based system identification method for dual-rate sampling Hammerstein quantized systems is presented by employing repeated stochastic empirical output measurements. The model features of dual-rate Hammerstein sampling system and a two-step identification strategy are first presented under relaxed estimated error condition. The persistent exciting condition for parameter identification is derived. The auxiliary model based parameter recursive identification algorithm for dual-rate sample Hammerstein nonlinear quantized systems is also given then. Convergence analysis of the auxiliary model based quantized identification recursive algorithm provides an upper bound value for parameter identification error estimation. Finally,simulation results show the effectiveness of the conclusions.
output signal quantization Hammerstein nonlinear system dual-rate sampling system repeated stochastic empirical system identification
Zhang Tao Xie Linbo Ding Feng
School of communication and control engineering, Jiangnan University, Wuxi Jiangsu 214122,China
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
785-790
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）