Identification of switching systems using change detection technique in the subspace framework

Pékpé, Komi Midzodzi; Mourot, Gilles; Gasso, Komi; Ragot, José

doi:10.1109/cdc.2004.1429317

Cited by 30 publications

(20 citation statements)

References 2 publications

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“…Using the estimates Φ(t) and θ in place of Φ(t) and θ in the above equation, v(t) can be calculated by v(t) = y(t) − ( Φ(t)) T θ(t). (25) Thus, the recursive gradient identification algorithm based on auxiliary model (RGA-AM) can be employed to confirm the parameters of (13).…”

Section: Parameters Estimationmentioning

confidence: 99%

“…In [12], the subspace projection based on orthogonal decomposition was adopted to judge which mode is switched. A novel clustering technique was presented to solve MD by calculating the errors between the samples and the output of each mode in [13]. For the online identification of SLS, some researchers have given attention to this problem and have demonstrated their results.…”

Section: Introductionmentioning

confidence: 99%

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Identification algorithm of switched systems based on generalized auxiliary model

Wang¹,

Xia²

2019

Jsee

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For switched linear system with colored measurement noises, the identification difficulties of this system are that there exist unknown switching information, unknown middle variables and noise terms in the information vector. For the mentioned issues, the fuzzy clustering and the multi-innovation recursive identification algorithm are used to deal with these problems. Firstly, the mode detection is transformed into the detection of membership degree values confirmed by the fuzzy clustering method, and the problem of mode detection is solved by judgment and decision of the fuzzy membership values. Moreover, the multi-innovation recursive identification algorithm based on the generalized auxiliary model is proposed to estimate the parameters of the switched linear system with colored noises. Finally, the effectiveness of the proposed method is verified by the results of the simulation example.

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Section: Parameters Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification algorithm of switched systems based on generalized auxiliary model

Wang¹,

Xia²

2019

Jsee

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“…When the switches are separated by a certain minimum time, subspace identification, coupled with detection techniques have been shown to be operative in batch mode. Among others, Huang, Wagner, and Ma (2004); Pekpe, Mourot, Gasso, and Ragot (2004); Verdult and Verhaegen (2004) and Borges, Verdult, Verhaegen, and Botto (2005) addressed recently this problem in an off-line context. Notice that in this case, as the continuous state is generally unknown, there is no available regression vector so that partitioning the regression space (here the state-input space) becomes harder.…”

Section: Introductionmentioning

confidence: 98%

On-line structured subspace identification with application to switched linear systems

Bako

Mercère

Lecœuche

2009

International Journal of Control

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This article is concerned with the identification of switched linear multiple-inputs-multiple-outputs state-space systems in a recursive way. First, a structured subspace identification scheme for linear systems is presented which turns out to have many attractive features. More precisely, it does not require any singular value decomposition but is derived using orthogonal projection techniques; it allows a computationally appealing implementation and it is closely related to input-output models identification. Second, it is shown that this method can be implemented on-line to track both the range space of the extended observability matrix and its dimension and thereby, the system matrices. Third, by making use of an on-line switching times detection strategy, this method is applied to blindly identify switched systems and to label the obtained submodels. Simulation results on noisy data illustrate the abilities and the benefits of the proposed approach.

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“…In the off-line context, among the various strategies developed [10], [14], [15], [16], [17] highlight the works using switching detection techniques [15], [16], [17]. Basically, in these works the initial step is the application of an algorithm to detect the switching times of the system.…”

Section: Introductionmentioning

confidence: 99%

New algorithm for identification of discrete-time switched linear systems

Lopes

Borges

Ishihara

2013

2013 American Control Conference

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This paper addresses the problem of the identification of discrete-time switched linear MIMO state space systems. The methodology proposed explores the use of subspace identification techniques, clustering and classification of data to estimate the quantity, a matrix representation of the sub-models and an estimate of the instants of switching of the system. An important feature of the algorithm is that the matrices of the different sub-models can be directly combined because they are obtained for the same base states. The efficiency of the developed method is illustrated using a numerical simulation.

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Identification of switching systems using change detection technique in the subspace framework

Cited by 30 publications

References 2 publications

Identification algorithm of switched systems based on generalized auxiliary model

Identification algorithm of switched systems based on generalized auxiliary model

On-line structured subspace identification with application to switched linear systems

New algorithm for identification of discrete-time switched linear systems

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