2018/04/27 by M. Mohsin Siraj, Siraj, M. Mohsin, Max Potters +3
Decision Sciences · Engineering · #Advanced Control Systems Optimization #Control Systems and Identification #FOS: Electrical engineering #Fault Detection and Control Systems #Probabilistic and Robust Engineering Design #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1804.10389
openalex publication_date 2018/04/27 · openalex created_date 2022/09/01 · openalex updated_date 2026/07/28
Recent developments in science and engineering have motivated control systems\nto be considered as interconnected and networked systems. From a system\nidentification point of view, modelling of a local module in such a structured\nsystem is a relevant and interesting problem. This work focuses on the quality,\nin terms of variance, of an estimate of a local module. We analyse which\npredictor input signals are relevant and contribute to variance reduction,\nwhile still guaranteeing the consistency of the estimate. For a targeted local\nmodule, a comparison of its estimate variance is made between a full-MISO\napproach and an immersed network setting, where a reduced number of inputs is\nused, while still guaranteeing consistency. A case study of a four-node network\nis considered and it is shown that a smaller set of predictor inputs can, under\nsome conditions, result in a smaller variance compared to the full-MISO\napproach.\n