Abstract
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.
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