Closed‐Loop Identification for Control of Linear Parameter Varying Systems

Bendtsen, Jan Dimon; Trangbaek, Klaus

doi:10.1002/asjc.612

Cited by 9 publications

(8 citation statements)

References 29 publications

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“…On the other hand, it has been assumed that there is no variation in the system represented by G; when doing controller switching in a system with variations the dual YK formulation needs also to be employed. All the plants stabilized by a given controller are represented by G(S), where S is the dual YK parameter [17]. In that case, CL stability involves both Q and S: (I − QS) −1 ∈ RH ∞ [5].…”

Section: Structures 7 Andmentioning

confidence: 99%

Youla-Kucera Control Structures for Switching

Navas

Mahtout

Milanés

et al. 2018

2018 IEEE Conference on Control Technology and Applications (CCTA)

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This paper explores the different controller structures in connection with Youla-Kucera (YK) parameterization to provide stable controller reconfiguration. Mathematical stability proof is given for each of the structures. Even if stability is guaranteed, transient effects of switching between controllers can become important for the system performance. Thus, transient behavior depending on the control structure is also analysed. A comparative study is carried out among all the structures, so guidelines are given on how to choose the appropriate YK control structure.

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Section: Structures 7 Andmentioning

confidence: 99%

Youla-Kucera Control Structures for Switching

Navas

Mahtout

Milanés

et al. 2018

2018 IEEE Conference on Control Technology and Applications (CCTA)

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“…The original method in [10] for LTI systems is extended for LPV systems in [11]. This method is used here once double coprime factorization of the controller/model set is obtained.…”

Section: B Hansen Scheme For Lpv Systemsmentioning

confidence: 99%

“…Using the Hansen scheme proposed in [10], one can transform the CL problem into an OL-like identification problem. The same has been used and extended to LPV systems [11] inside of the Danish research program entitled Plug and Play Process Control [12]. Identification of coupled dynamics in heat distribution systems [13], and identification of actuators/sensors in the latter [14] were carried out into the project, showing promising model results.…”

Section: Introductionmentioning

confidence: 99%

Youla-Kucera based online closed-loop identification for longitudinal vehicle dynamics

Navas

Milanés

Nashashibi

2017

2017 21st International Conference on System Theory, Control and Computing (ICSTCC)

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Abstract-This paper deals with the identification of longitudinal dynamics of a cycab for subsequent control performance's improvement. Low-speed vehicle dynamic is used as physical model which non-linear behavior is highly complex to properly identify. Among several identification techniques, closed-loop identification gives better performance in a model-based control design. Here, the Hansen scheme is used to transform a closedloop identification problem in an open-loop-like. The algorihtm is tested in a string of two cycabs equipped with a proportionalderivative-based cooperative adaptive cruise controller, showing how the resulting model is improved in comparison with an openloop identification algorithm-ARX model.

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“…Because of the correlation between the noise and the input of the plant, the open loop methods usually cannot be used to estimate the closed-loop system accurately [6][7][8][9]. The closed-loop estimation methods contain the direct method, the indirect method, and the joint inputoutput method [7,10,11].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Multi‐Order Spectra for Nonlinear Closed‐Loop Systems

Zhang

Cao

2017

Asian Journal of Control

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In this paper, a multi-order spectra estimation method is proposed for a nonlinear closed-loop system based on the Volterra series. Owing to the correlation between the noise and the input, the estimation accuracy is poor when the nonlinear spectra of the plant is obtained using the traditional estimation method. In order to overcome this problem, a two-step scheme is used to estimate the multi-order spectrum of a nonlinear system operating in closed-loop. Firstly, the generalized frequency response functions (GFRFs) from the reference signal to the input of the plant are estimated, and they are used to simulate the noise-free input spectra of the plant. Secondly, the GFRFs of the controlled plant are estimated using the noise-free input spectra and the output spectra. Because the GFRFs are multidimensional functions, the required amount of calculation for the estimation is very large. To reduce computational complexity, a simplified GFRF model is adopted to estimate the multi-order nonlinear spectrum of the plant. In this model, the GFRF is transformed to a one-dimensional function. Two simulation experiments are provided to illustrate the proposed approach.

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Closed‐Loop Identification for Control of Linear Parameter Varying Systems

Cited by 9 publications

References 29 publications

Youla-Kucera Control Structures for Switching

Youla-Kucera Control Structures for Switching

Youla-Kucera based online closed-loop identification for longitudinal vehicle dynamics

Estimation of Multi‐Order Spectra for Nonlinear Closed‐Loop Systems

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