Identification of Hammerstein Systems With Dead-Zone Nonlinearities Using Modified CPLNN
会议名称：《第二十九届中国控制会议》
会议日期：2010年
学科分类：0711[理学-系统科学] 07[理学] 071102[理学-系统分析与集成]
基 金：supported by National Nature Science Foundation under Grant 60974046
关 键 词：Hammerstein System Non-Symmetric Dead-Zone Continuous Piecewise Linear Neural Network(CPLNN) Identification
摘 要：A new one-stage identification method is proposed for Hammerstein systems in presence of non-symmetric dead-zone input nonlinearities.A modified continuous piecewise linear neural network whose activation functions are specified as the max-min linear functions is employed to describe the dead-zone *** a united parameterized model is derived to represent the entire ***-zone parameters（thresholds and slopes）as well as the linear subsystem parameters can be calculated according to the proposed *** main differences between the present method and the commonly used recursive methods lie in that the proposed model can be built without separating the nonlinear part from the linear part and no iteration procedure is needed in the parameter *** method can be used without a priori knowledge of the dead-zone and is suitable for the modeling of Hammerstein systems with black-box nonlinear *** experiments are presented to illustrate that it can be a promising tool for identifying Hammerstein systems with dead-zone nonlinearities.