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A Non-Parametric Linear Parameter Varying Approach for Identification of Linear Time-Varying Systems *

机译:用于识别线性时变系统的非参数线性参数可变方法 *

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This paper presents a novel, non-parametric, linear parameter varying (LPV) algorithm for identification of linear time-varying systems. The method estimates the timevarying impulse response function as a LPV Laguerre basis expansion whose coefficients are functions of a scheduling variable (SV). Unlike many parametric LPV identification techniques, the method requires no a priori knowledge of the system order. Monte Carlo simulations of a time-varying, second-order system mimicking variations of reex stiffness dynamics with ankle position demonstrated that the method performs very well. It will be a valuable tool for identification of physiological and engineering systems in conditions where the system order is unknown and its parameters change with a SV.
机译:本文提出了一种新颖的非参数线性参数变化(LPV)算法,用于识别线性时变系统。该方法将时变脉冲响应函数估计为LPV Laguerre基展开,其系数是调度变量(SV)的函数。与许多参数LPV识别技术不同,该方法不需要系统顺序的先验知识。时变的二阶系统的蒙特卡洛模拟模拟了reex刚度动力学随脚踝位置的变化,证明了该方法的效果很好。在系统顺序未知且参数随SV变化的情况下,它将是鉴定生理和工程系统的宝贵工具。

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