Continuous-time subspace identification in closed-loop

This paper deals with the problem of continuoustime model identification and presents a subspace-based algorithm capable of dealing with data generated by systems operating in closed-loop. The algorithm is developed by reformulating the identification problem from the continuous-time model to an equivalent one to which discrete-time subspace identification techniques can be applied. More precisely, the considered approach corresponds to the projection of the input-output data onto an orthonormal basis, defined in terms of Laguerre filters. In this framework, the PBSID subspace identification algorithm, originally developed in the case of discrete-time systems, can be reformulated for the continuoustime case. Simulation results are used to illustrate the achievable performance of the proposed approach with respect to existing methods available in the literature.

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