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A set of flexible basis functions that generalizes the classical Laguerre and Kautz bases is shown to possess attractive properties when used in linear least-squares identification. Abstract-A least-squares identification method is studied that estimates a finite number of expansion coefficients in the series expansion of a transfer function, where the(More)
— In this paper the robust detection filter design problem as a scaled H ∞ filtering problem is presented where the effect of estimation weighting on filtering performance is optimized through input diagonal scaling of the estimation. The objective is that, by the proper choice of the estimation weight, provide the smallest scaled L 2 gain of the(More)
In this paper the classical detection filter design problem is considered as an input reconstruction problem. Input reconstruction is viewed as a dynamic inversion problem. This approach is based on the existence of the left inverse and arrives at detector architectures whose outputs are the fault signals while the inputs are the measured system inputs and(More)