2016
DOI: 10.1016/j.automatica.2016.05.027
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Subsystem identification of multivariable feedback and feedforward systems

Abstract: We present a frequency-domain technique for identifying multivariable feedback and feedforward subsystems that are interconnected with a known subsystem. This subsystem identification algorithm uses closed-loop input-output data, but no other system signals are assumed to be measured. In particular, neither the feedback signal nor the outputs of the unknown subsystems are assumed to be measured. We use a candidate-pool approach to identify the feedback and feedforward transfer function matrices, while guarante… Show more

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Cited by 17 publications
(4 citation statements)
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“…The first method for ICSI is performed manually and is known as conventional ICSI [25][26][27][28][29][30][31][32][33][34][35]. With this technique, the tip of the injection pipette is approaching gently towards the cell membrane about halfway or even much further into the oocyte.…”
Section: Conventional Icsimentioning
confidence: 99%
“…The first method for ICSI is performed manually and is known as conventional ICSI [25][26][27][28][29][30][31][32][33][34][35]. With this technique, the tip of the injection pipette is approaching gently towards the cell membrane about halfway or even much further into the oocyte.…”
Section: Conventional Icsimentioning
confidence: 99%
“…Multivariable closed-loop systems can be effectively handled by state space models, decentralized identification, and subsystem identification. Notably, the abovementioned studies were based on a controller order that satisfies identifiable conditions [10][11][12]. However, a multivariable closed-loop system whose controller order is lower than that of the process without interference noise in the feedback channel has not elicited much attention.…”
Section: Introductionmentioning
confidence: 99%
“…However, a multivariable closed-loop system whose controller order is lower than that of the process without interference noise in the feedback channel has not elicited much attention. The real issue lies in the linear correlation existing in the elements of the measured data vector through the feedback in multivariable systems, and this leads to the unidentifiability of the parameters [12]. This situation is inevitable in practice, but only a few studies have been conducted on this aspect.…”
Section: Introductionmentioning
confidence: 99%
“…For example, Zhang and Hoagg used a candidate-pool approach to identify the feedback and feedforward transfer function matrices and presented a frequency-domain technique for identifying multivariable feedback and feedforward systems [8]; Salhi and Kamoun proposed a recursive algorithm to estimate the parameters of the dynamic linear part and the static nonlinear part of multivariable Hammerstein systems [9].…”
Section: Introductionmentioning
confidence: 99%