Abstract
For many industrial production processes, safety and production restrictions are often strong reasons for not allowing identification experiments in open loop. In such situations, experimental data can only be obtained under closed-loop conditions. The main difficulty in closed-loop identification is due to the correlation between the disturbances and the control signal, induced by the loop. Several alternatives are available to cope with this problem, broadly classified into three main approaches: direct, indirect and joint input-output [9, 14]. Some particular versions of these methods have been developed more recently in the area of control-relevant identification as, e.g., the two-stage, the coprime factor and the dual-Youla methods. An overview of these recent developments can be found in [2] and [19].
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Gilson, M., Garnier, H., Young, P.C., Van den Hof, P. (2008). Instrumental Variable Methods for Closed-loop Continuous-time Model Identification. In: Garnier, H., Wang, L. (eds) Identification of Continuous-time Models from Sampled Data. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-84800-161-9_5
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DOI: https://doi.org/10.1007/978-1-84800-161-9_5
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