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— The aim of this paper is to propose an instrumental variable (IV) solution for wide-band frequency domain identification. The focus is first on the extension of the refined IV method for continuous-time model identification to the frequency domain. Then, an iterative IV scheme coupled with an appropriate frequency localising basis function is developed to(More)
Identification of linear parameter-varying systems in an input-output setting is investigated, focusing on the case when the noise part of the data generating system is an additive colored noise. In the Box-Jenkins and output-error cases, it is shown that the currently available linear regression and instrumental variable methods from the literature are far(More)
Keywords: Linear parameter-varying systems System identification Refined instrumental variable Box–Jenkins models a b s t r a c t Identification of real-world systems is often applied in closed loop due to stability, performance or safety constraints. However, when considering Linear Parameter-Varying (LPV) systems, closed-loop identification is not(More)
— This article presents instrumental variable methods for direct continuous-time estimation of a Hammerstein model. The non-linear function is a sum of known basis functions and the linear part is a Box–Jenkins model. Although the presented algorithm is not statistically optimal, this paper further shows the performance of the presented algorithms and the(More)
— This paper considers the problem of continuous-time model identification with arbitrary time-delay from irregularly sampled data. The proposed method estimates the plant and the time-delay in a separable way, when estimating one of them, the other is assumed to be fixed. More precisely, the plant is estimated by the iterative instrumental variable SRIVC(More)