Identification for robust <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si9.gif" display="inline" overflow="scroll"><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:math> deconvolution filtering

Bombois, Xavier; Hjalmarsson, Håkan; Scorletti, Gérard

doi:10.1016/j.automatica.2010.01.023

Cited by 16 publications

(1 citation statement)

References 13 publications

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“…System identification for robust control allows comparing the performance of the unknown real system loop with a controller tuned using an identified plant model. The least-costly identification experiment for control, where the main goal is to design an experiment that ensures a small enough uncertainty region but still provides an acceptable performance of control, was proposed in [7,8]. It was found that, during the advanced control loop designs, model construction absorbs approximately 75% of the costs [9].…”

Section: Introductionmentioning

confidence: 99%

Free Final Time Input Design Problem for Robust Entropy-Like System Parameter Estimation

Jakowluk

2018

Entropy

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In this paper, a novel method is proposed to design a free final time input signal, which is then used in the robust system identification process. The solution of the constrained optimal input design problem is based on the minimization of an extra state variable representing the free final time scaling factor, formulated in the Bolza functional form, subject to the D-efficiency constraint as well as the input energy constraint. The objective function used for the model of the system identification provides robustness regarding the outlying data and was constructed using the so-called Entropy-like estimator. The perturbation time interval has a significant impact on the cost of the real-life system identification experiment. The contribution of this work is to examine the economic aspects between the imposed constraints on the input signal design, and the experiment duration while undertaking an identification experiment in the real operating conditions. The methodology is applicable to the general class of systems and was supported by numerical examples. Illustrative examples of the Least Squares, and the Entropy-Like estimators for the system parameter data validation where measurements include additive white noise are compared using ellipsoidal confidence regions.

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Section: Introductionmentioning

confidence: 99%

Free Final Time Input Design Problem for Robust Entropy-Like System Parameter Estimation

Jakowluk

2018

Entropy

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Adaptive control and signal processing literature survey (No. 18)

2010

Adaptive Control & Signal

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In order to keep readers up-to-date, the journal will contain a list of recently published journal articles relevant to the fields of adaptive control and signal processing six times a year. This list is compiled from a wide range of journals. Please note that although the list has been broadly categorized, these classifications are by no means strict, and are there to assist the reader. Please also note that inclusion in the list is not an endorsement of a paper's quality. If you have any suggestions or comments, please e-mail Erfu Yang at erfu.yang@eee.strath.ac.uk. ADAPTIVE SYSTEMSBaldi S, Battistelli G, Mosca E, Tesi P. Multi-model unfalsified adaptive switching supervisory control. Automatica 2010; 46(2):249-259. Cao C, Hovakimyan N. Stability margins of L 1 adaptive control architecture. IEEE Transactions on Automatic Control 2010; 55(2):480-487. Chen W, Jiao L. Adaptive tracking for periodically time-varying and nonlinearly parameterized systems using multilayer neural networks. IEEE Transactions on Neural Networks 2010; 21(2):345-351. Han T-T, Ge S, Lee T. Persistent dwell-time switched nonlinear systems: variation paradigm and gauge design. IEEE Transactions on Automatic Control 2010; 55(2):321-337. Li L, Petersen I. A Gramian-based approach to model reduction for uncertain systems. IEEE Transactions on Automatic Control 2010; 55(2):508-514. Li Q-K, Zhao J, Dimirovski G, Liu X-J. State convergence property of perturbed switched linear time-delay systems. IET Control Theory and Applications 2010; 4(2):273-281. Li T-S, Tong S-C, Feng G. A novel robust adaptive-fuzzytracking control for a class of nonlinear multi-input/multioutput systems. IEEE Transactions on Fuzzy Systems 2010; 18(1):150-160. Ma H-J, Yang G-H. Adaptive output control of uncertain nonlinear systems with non-symmetric dead-zone input. Automatica 2010; 46(2):413-420. Niedzwiecki M. Generalized adaptive notch smoothing revisited. IEEE Transactions on Signal Processing 2010; 58(3):1565-1576. Obaidat M, Misra S, Papadimitriou G. Adaptive and learning systems. IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetic 2010; 40(1):2-5. Yang Z-J, Hara S, Kanae S, Wada K, Su C-Y. An adaptive robust nonlinear motion controller combined with disturbance observer. IEEE Transactions on Control Systems Technology 2010; 18(2):454-462. Yildiz Y, Annaswamy A, Kolmanovsky L, Yanakiev D. Adaptive posicast controller for time-delay systems with relative degree n * 2. Automatica 2010; 46(2):279-289. Zhang W-A, Yu L. Stabilization of sampled-data control systems with control inputs missing. IEEE Transactions on Automatic Control 2010; 55(2):447-452. 2. SIGNAL PROCESSING Aboutanios E. Estimation of the frequency and decay factor of a decaying exponential in noise. IEEE Transactions on Signal Processing 2010; 58(2):501-509. Addesso P, Marano S, Matta V. Estimation of target location via likelihood approximation in sensor networks. IEEE Transactions on Signal Processing 2010; 58(3):1358-1368. Bai K, Tepedelenlioglu C. Distributed detection in UWB wireles...

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Design of an Optimal Input Signal for Parameter Estimation of Linear Fractional-Order Systems

Jakowluk

2019

Lecture Notes in Electrical Engineering

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Identification for robust H2 deconvolution filtering

Cited by 16 publications

References 13 publications

Free Final Time Input Design Problem for Robust Entropy-Like System Parameter Estimation

Free Final Time Input Design Problem for Robust Entropy-Like System Parameter Estimation

Adaptive control and signal processing literature survey (No. 18)

Design of an Optimal Input Signal for Parameter Estimation of Linear Fractional-Order Systems

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