Searched for: author:"Verhaegen, M.H.G."
(1 - 8 of 8)
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Yu, C. (author), Chen, Jie (author), Ljung, Lennart (author), Verhaegen, M.H.G. (author)
The continuous-time subspace identification using state-variable filtering has been investigated for a long time. Due to the simple orthogonal basis functions that were adopted by the existing methods, the identification performance is quite sensitive to the selection of the system-dynamic parameter associated with an orthogonal basis. To...
conference paper 2017
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Yu, C. (author), Ljung, Lennart (author), Verhaegen, M.H.G. (author)
Gray-box identification is prevalent in modeling physical and networked systems. However, due to the non-convex nature of the gray-box identification problem, good initial parameter estimates are crucial for a successful application. In this paper, a new identification method is proposed by exploiting the low-rank and structured Hankel matrix...
conference paper 2017
document
Yu, C. (author), Verhaegen, M.H.G. (author)
Abstract:<br/>This note studies the identification of individual systems operating in a large-scale distributed network by considering the interconnection signals between neighboring systems to be unmeasurable. The unmeasurable interconnections act as unknown system inputs to the individual systems in a network, which poses a challenge for the...
journal article 2017
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Yu, C. (author), Verhaegen, M.H.G. (author)
This note studies the identification of a network comprised of interconnected clusters of LTI systems. Each cluster consists of homogeneous dynamical systems, and its interconnections with the rest of the network are unmeasurable. A subspace identification method is proposed for identifying a single cluster using only local input and output data...
journal article 2017
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Yu, C. (author), Verhaegen, M.H.G. (author)
In this paper, we study the deterministic blind identification of multiple channel state-space models having a common unknown input using measured output signals that are perturbed by additive white noise sequences. Different from traditional blind identification problems, the considered system is an autoregressive system rather than an FIR...
journal article 2016
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Yu, C. (author), Verhaegen, M.H.G. (author)
This paper studies the local identification of large-scale homogeneous systems<br/>with general network topologies. The considered local system identification problem involves unmeasurable signals between neighboring subsystems. Compared with our previous work in Yu et al. (2014) which solves the local identification of 1D homogeneous systems,...
conference paper 2015
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Yu, C. (author), Verhaegen, M.H.G. (author), Hansson, A (author)
This paper studies the local subspace identification of 1D homogeneous networked systems. The main challenge lies at the unmeasurable interconnection signals between neighboring subsystems. Since there are many unknown inputs to the concerned local system, the corresponding identification problem is semi-blind. To cope with this problem, a...
conference paper 2015
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Yu, C. (author), Verhaegen, M.H.G. (author), Kovalsky, S (author), Basri, R (author)
The identification of structured state-space model has been intensively studied for a long time but still has not been adequately addressed. The main challenge is that the involved estimation problem is a non-convex (or bilinear) optimization problem. This paper is devoted to developing an identification<br/>method which aims to find the global...
conference paper 2015
Searched for: author:"Verhaegen, M.H.G."
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