PMF-Based Subspace Method for Continuous-Time Model Identification Deterministic Study

Bastogne, Thierry; Garnier, Hugues; Sibille, P.; Mensler, M.

doi:10.1016/s1474-6670(17)43064-3

Cited by 15 publications

(21 citation statements)

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“…A necessary and sufficient condition for a system to have a finite-dimensional observation space is to be immersed into a linear observable system 7 . By definition, this amounts to saying that there exists a (sufficiently) smooth mapping y : X !…”

Section: A Preliminary Discussionmentioning

confidence: 99%

“…With the exception of minor modifications, the approach proposed below is borrowed from [5] and adapted to the continuous-time scenario. Different subspace identification methods for continuous-time linear systems can be found in [6][7][8].…”

Section: Subspace Identification For Autonomous Linear Systemsmentioning

confidence: 99%

“…With these modifications, in view of Assumption 2, the number of time derivatives of output measurements required for the construction of the output matrix Y i,j is drastically reduced. Strategies similar to one described above have been combined with dedicated filtering techniques to design subspace identification algorithms for continuoustime linear systems in [6][7][8]. The approaches proposed in these works are undoubtedly suitable for practical implementation.…”

Section: Subspace Identification For Autonomous Linear Systemsmentioning

confidence: 99%

“…to develop continuous-time counterparts of subspace identification methods [6][7][8]. However, the characterisation of their applicability to general nonlinear systems is still an open problem.…”

mentioning

confidence: 99%

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Towards deterministic subspace identification for autonomous nonlinear systems

Padoan

Astolfi

2015

2015 54th IEEE Conference on Decision and Control (CDC)

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Abstract-The problem of identifying deterministic autonomous linear and nonlinear systems is studied. A specific version of the theory of deterministic subspace identification for discrete-time autonomous linear systems is developed in continuous time. By combining the subspace approach to linear identification and the differentialgeometric approach to nonlinear control systems, a novel identification framework for continuous-time autonomous nonlinear systems is developed.

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Section: A Preliminary Discussionmentioning

confidence: 99%

Section: Subspace Identification For Autonomous Linear Systemsmentioning

confidence: 99%

Section: Subspace Identification For Autonomous Linear Systemsmentioning

confidence: 99%

mentioning

confidence: 99%

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Towards deterministic subspace identification for autonomous nonlinear systems

Padoan

Astolfi

2015

2015 54th IEEE Conference on Decision and Control (CDC)

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“…Both methods are extensions of methods presented in the literature for rational (thus non fractional) systems [6,8,9] to the fractional case. Other subspace techniques for identifying continuous-time rational models can be found in [2,16,11,15]. So, the proposed method inherits the advantages of subspace methods which stem from the reliability of numerical algorithms using the QR and the singular value decompositions [10].…”

Section: Introductionmentioning

confidence: 99%

Differentiation similarities in fractional pseudo-state space representations and the subspace-based methods

Malti

Thomassin

2013

fcaa

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The paper starts by presenting a new concept of differentiation similarity transformations for commensurate pseudo-states-space representations. It is proven that a pseudo-state-space representation with a commensurate differentiation order ν and a dimension of the transition matrix n can be similar to a pseudo-state-space representation with a commensurate order ν/k and a dimension of the transition matrix kn, where k is an integer number. A direct consequence of the aforementioned concept in fractional subspace-based identification methods for MIMO systems is that an overestimated pseudo-state-space representation has multiple minimums at commensurate differentiation orders over the integral number k. This result is especially visible when deterministic input/output signals are considered and less visible in the stochastic case due to overestimation.MSC 2010 : Primary 26A33, Secondary 93B30

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Closed-Loop Identification and Control of Inland Vessels

Padilla

Bittner

Yuz

2015

Operations Research/Computer Science Interfaces Series

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Extensive research has been conducted on a navigation system for inland vessels at the University of Stuttgart and at the Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg (Focus Max Planck Gesellschaft, Computer at the helm, http://www.mpg.de/942027). As part of this navigation system, a model-based track-keeping controller has been developed. A high performance controller is required because of the reduced space available on rivers and canals. The control structure consists of two components, a feedback and a feedforward block, where the former is provided by a linear quadratic gaussian controller. Both components require the ship dynamics model and thus, the parameter estimation of the underlying model is a key issue to achieve high performance. In this chapter, we firstly consider Monte Carlo simulations to generate data of the closed-loop system and then the parameters of a continuous-time steering dynamics model are identified. The parameter estimation problem is solved applying an instrumental variable method, which takes into account the control structure. Parameter identification using real closed-loop experiments is also considered. Additionally, we evaluate the experiments for parameter estimation through a sensitivity analysis.

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PMF-Based Subspace Method for Continuous-Time Model Identification Deterministic Study

Cited by 15 publications

References 1 publication

Towards deterministic subspace identification for autonomous nonlinear systems

Towards deterministic subspace identification for autonomous nonlinear systems

Differentiation similarities in fractional pseudo-state space representations and the subspace-based methods

Closed-Loop Identification and Control of Inland Vessels

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