A general framework for least-squares based identification of time-varying system using multiple models

In this paper, a general framework for the identification of discrete-time time-varying system is proposed. To make the problem tractable, the time variation is approximated by a piecewise constant function assuming finite number N of unknown values. The algorithms proposed would be applicable for switched system with linear and nonlinear subsystems. It also facilitates the derivation of both offline and online parameter identification algorithms. Extensive simulation studies show that our algorithm can indeed provide accurate estimates of the plant parameters even in noisy cases. A preliminary convergence analysis is also available, which we would further develop in the near future.