Documents disponibles écrits par cet auteur

Reliability-based design using two-stage stochastic optimization with a treatment of model prediction errors / Alexandros A. Taflanidis in Journal of engineering mechanics, Vol. 136 N° 12 (Décembre 2010) 

Public ISBD [article]  in Journal of engineering mechanics > Vol. 136 N° 12 (Décembre 2010) . - pp.1460-1473 Titre : Reliability-based design using two-stage stochastic optimization with a treatment of model prediction errors Type de document : texte imprimé Auteurs : Alexandros A. Taflanidis, Auteur ; James L. Beck, Auteur Année de publication : 2011 Article en page(s) : pp.1460-1473 Note générale : Mécanique appliquée Langues : Anglais (eng) Mots-clés : Stochastic  models  Optimization  Simulation  System  reliability. Résumé : Design problems that involve optimization of the reliability of engineering systems are the focus of this paper. Methodologies are discussed applicable to problems that involve nonlinear systems and a large number of uncertain parameters specifying the system and excitation models. To address the complexity of these problems, stochastic simulation is considered for evaluation of the system reliability. An innovative approach, called stochastic subset optimization (SSO), is discussed for performing a sensitivity analysis with respect to the design variables of the problem as well as the uncertain model parameters. In a small number of iterations, SSO converges to a smaller subset of the original design space that has high plausibility of containing the optimal design variables and that consists of near-optimal designs. For higher accuracy, an appropriate stochastic optimization algorithm may then be used to pinpoint the optimal design variables within this subset. This produces an efficient two-stage framework for optimal reliability design. Topics related to the combination of the two different stages for overall enhanced efficiency are discussed. An example is presented that illustrates the effectiveness of the proposed two-stage methodology for a challenging dynamic reliability problem. Also, a study is performed of the influence on the optimal design decisions of the prediction error of the system model, which is introduced because no model makes perfect predictions of the system response. DEWEY : 620.1 ISSN : 0733-9399 En ligne : http://ascelibrary.org/emo/resource/1/jenmdt/v136/i12/p1460_s1?isAuthorized=no [article] Reliability-based design using two-stage stochastic optimization with a treatment of model prediction errors [texte imprimé] / Alexandros A. Taflanidis, Auteur ; James L. Beck, Auteur . - 2011 . - pp.1460-1473. Mécanique appliquée Langues : Anglais (eng) in Journal of engineering mechanics > Vol. 136 N° 12 (Décembre 2010) . - pp.1460-1473 Mots-clés : Stochastic  models  Optimization  Simulation  System  reliability. Résumé : Design problems that involve optimization of the reliability of engineering systems are the focus of this paper. Methodologies are discussed applicable to problems that involve nonlinear systems and a large number of uncertain parameters specifying the system and excitation models. To address the complexity of these problems, stochastic simulation is considered for evaluation of the system reliability. An innovative approach, called stochastic subset optimization (SSO), is discussed for performing a sensitivity analysis with respect to the design variables of the problem as well as the uncertain model parameters. In a small number of iterations, SSO converges to a smaller subset of the original design space that has high plausibility of containing the optimal design variables and that consists of near-optimal designs. For higher accuracy, an appropriate stochastic optimization algorithm may then be used to pinpoint the optimal design variables within this subset. This produces an efficient two-stage framework for optimal reliability design. Topics related to the combination of the two different stages for overall enhanced efficiency are discussed. An example is presented that illustrates the effectiveness of the proposed two-stage methodology for a challenging dynamic reliability problem. Also, a study is performed of the influence on the optimal design decisions of the prediction error of the system model, which is introduced because no model makes perfect predictions of the system response. DEWEY : 620.1 ISSN : 0733-9399 En ligne : http://ascelibrary.org/emo/resource/1/jenmdt/v136/i12/p1460_s1?isAuthorized=no

Reliability-based performance objectives and probabilistic robustness in structural control applications / Alexandros A. Taflanidis in Journal of engineering mechanics, Vol. 134 N°4 (Avril 2008) 

Public ISBD [article]  in Journal of engineering mechanics > Vol. 134 N°4 (Avril 2008) . - pp.291–301. Titre : Reliability-based performance objectives and probabilistic robustness in structural control applications Type de document : texte imprimé Auteurs : Alexandros A. Taflanidis, Auteur ; Jeffrey T. Scruggs, Auteur ; James L. Beck, Auteur Année de publication : 2008 Article en page(s) : pp.291–301. Note générale : Mécanique appliquée Langues : Anglais (eng) Mots-clés : Structural  control  Reliability  Optimization  design  Probability Résumé : A reliability-based structural control design approach is presented that optimizes a control system explicitly to minimize the probability of structural failure. Failure is interpreted as the system’s state trajectory exiting a safe region within a given time duration. This safe region is bounded by hyperplanes in the system state space, each of them corresponding to an important response quantity. An efficient approximation is discussed for the analytical evaluation of this probability, and for its optimization through feedback control. This analytical approximation facilitates theoretical discussions regarding the characteristics of reliability-optimal controllers. Versions of the controller design are described for the case using a nominal model of the system, as well as for the case with uncertain model parameters. For the latter case, knowledge about the relative plausibility of the different possible values of the uncertain parameters is quantified through the use of probability distributions on the uncertain parameter space. The influence of the excitation time duration on feedback control design is discussed and a probabilistic treatment of this time duration is suggested. The relationship to H2 (i.e., minimum variance) controller synthesis is also examined. ISSN : 0733-9399 En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%290733-9399%282008%29134%3A4%2829 [...] [article] Reliability-based performance objectives and probabilistic robustness in structural control applications [texte imprimé] / Alexandros A. Taflanidis, Auteur ; Jeffrey T. Scruggs, Auteur ; James L. Beck, Auteur . - 2008 . - pp.291–301. Mécanique appliquée Langues : Anglais (eng) in Journal of engineering mechanics > Vol. 134 N°4 (Avril 2008) . - pp.291–301. Mots-clés : Structural  control  Reliability  Optimization  design  Probability Résumé : A reliability-based structural control design approach is presented that optimizes a control system explicitly to minimize the probability of structural failure. Failure is interpreted as the system’s state trajectory exiting a safe region within a given time duration. This safe region is bounded by hyperplanes in the system state space, each of them corresponding to an important response quantity. An efficient approximation is discussed for the analytical evaluation of this probability, and for its optimization through feedback control. This analytical approximation facilitates theoretical discussions regarding the characteristics of reliability-optimal controllers. Versions of the controller design are described for the case using a nominal model of the system, as well as for the case with uncertain model parameters. For the latter case, knowledge about the relative plausibility of the different possible values of the uncertain parameters is quantified through the use of probability distributions on the uncertain parameter space. The influence of the excitation time duration on feedback control design is discussed and a probabilistic treatment of this time duration is suggested. The relationship to H2 (i.e., minimum variance) controller synthesis is also examined. ISSN : 0733-9399 En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%290733-9399%282008%29134%3A4%2829 [...]

Robust stochastic design of linear controlled systems for performance optimization / Alexandros A. Taflanidis in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 132 N° 5 (Septembre 2010) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 132 N° 5 (Septembre 2010) . - 15 p. Titre : Robust stochastic design of linear controlled systems for performance optimization Type de document : texte imprimé Auteurs : Alexandros A. Taflanidis, Auteur ; Scruggs, Jeffrey T., Auteur ; James L. Beck, Auteur Année de publication : 2010 Article en page(s) : 15 p. Note générale : Systèmes dynamiques Langues : Anglais (eng) Mots-clés : Control  system  synthesis  Linear  systems  Optimal  control  Robust  control  Stability  Structural  engineering  Vibration  control Index. décimale : 629.8 Résumé : This study discusses a robust controller synthesis methodology for linear, time invariant systems, under probabilistic parameter uncertainty. Optimization of probabilistic performance robustness for [script H]2 and multi-objective [script H]2 measures is investigated, as well as for performance measures based on first-passage system reliability. The control optimization approaches proposed here exploit recent advances in stochastic simulation techniques. The approach is illustrated for vibration response suppression of a civil structure. The results illustrate that, for problems with probabilistic uncertainty, the explicit optimization of probabilistic performance robustness can result in markedly different optimal feedback laws, as well as enhanced performance robustness, when compared to traditional “worst-case” notions of robust optimal control. DEWEY : 629.8 ISSN : 002-0434 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013200 [...] [article] Robust stochastic design of linear controlled systems for performance optimization [texte imprimé] / Alexandros A. Taflanidis, Auteur ; Scruggs, Jeffrey T., Auteur ; James L. Beck, Auteur . - 2010 . - 15 p. Systèmes dynamiques Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 132 N° 5 (Septembre 2010) . - 15 p. Mots-clés : Control  system  synthesis  Linear  systems  Optimal  control  Robust  control  Stability  Structural  engineering  Vibration  control Index. décimale : 629.8 Résumé : This study discusses a robust controller synthesis methodology for linear, time invariant systems, under probabilistic parameter uncertainty. Optimization of probabilistic performance robustness for [script H]2 and multi-objective [script H]2 measures is investigated, as well as for performance measures based on first-passage system reliability. The control optimization approaches proposed here exploit recent advances in stochastic simulation techniques. The approach is illustrated for vibration response suppression of a civil structure. The results illustrate that, for problems with probabilistic uncertainty, the explicit optimization of probabilistic performance robustness can result in markedly different optimal feedback laws, as well as enhanced performance robustness, when compared to traditional “worst-case” notions of robust optimal control. DEWEY : 629.8 ISSN : 002-0434 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013200 [...]