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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)
Abstract: By using the concept of parameter varying (C,A)-invariant subspace and parameter varying unobservability subspace, this paper investigates the problem of fault detection and isolation in linear parameter varying (LPV) systems. The so called detection filters approach, formulated as the fundamental problem of residual generation (FPRG) for linear(More)
Using induced L₂-norm minimization, a robust controller was developed for insulin delivery in Type I diabetic patients. The high-complexity nonlinear diabetic patient Sorensen-model was considered and Linear Parameter Varying methodology was used to develop open-loop model and robust H(∞) controller. Considering the normoglycaemic set point (81.1 mg/dL), a(More)
— This paper proposes a new approach to identification of the poles in a linear system from frequency domain data. The discrete rational transfer function is represented in a rational Laguerre–basis, where the basis elements can be expressed by powers of the Blaschke–function. This function can be interpreted as a congruence transform on the Poincaré unit(More)