This article presents a new identification method for discrete-time, single-input single-output, linear time-varying (LTV) plant utilizing the input and output data. This method applies specifically to plants that are able to repeat their trajectories. The identification learning law is determined through an optimization framework, which is similar in nature to the norm optimal design for Iterative Learning Control (ILC). Conditions for stability and convergence are obtained in the study. The design is verified using a numerical example.

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