Bibliographies thématiques / Perturbation-Based methods

Littérature scientifique sur le sujet « Perturbation-Based methods »

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Publié le 7 juillet 2024

Mis à jour le 7 juillet 2024

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Articles de revues sur le sujet "Perturbation-Based methods"

Hongxing, Li. « Fuzzy clustering methods based on perturbation ». Fuzzy Sets and Systems 33, n^o 3 (décembre 1989) : 291–302. http://dx.doi.org/10.1016/0165-0114(89)90119-x.

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Martinelli, M., A. Dervieux, L. Hascoet, V. Pascual et A. Belme. « AD-based perturbation methods for uncertainties and errors ». International Journal of Engineering Systems Modelling and Simulation 2, n^o 1/2 (2010) : 65. http://dx.doi.org/10.1504/ijesms.2010.031872.

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San-Juan, Juan Félix, Montserrat San-Martín, Iván Pérez et Rosario López. « Hybrid perturbation methods based on statistical time series models ». Advances in Space Research 57, n^o 8 (avril 2016) : 1641–51. http://dx.doi.org/10.1016/j.asr.2015.05.025.

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Chioua, Moncef, Bala Srinivasan, Michel Perrier et Martin Guay. « EFFECT OF EXCITATION FREQUENCY IN PERTURBATION-BASED EXTREMUM SEEKING METHODS ». IFAC Proceedings Volumes 40, n^o 5 (2007) : 123–28. http://dx.doi.org/10.3182/20070606-3-mx-2915.00019.

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Ivanovs, Maksims, Roberts Kadikis et Kaspars Ozols. « Perturbation-based methods for explaining deep neural networks : A survey ». Pattern Recognition Letters 150 (octobre 2021) : 228–34. http://dx.doi.org/10.1016/j.patrec.2021.06.030.

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Liu, Song-Tao, et Yuesheng Xu. « Galerkin Methods Based on Hermite Splines for Singular Perturbation Problems ». SIAM Journal on Numerical Analysis 43, n^o 6 (janvier 2006) : 2607–23. http://dx.doi.org/10.1137/040607411.

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El Mokhtari, Rachid, Jean-Marc Cadou et Michel Potier-Ferry. « A two grid algorithm based on perturbation and homotopy methods ». Comptes Rendus Mécanique 330, n^o 12 (décembre 2002) : 825–30. http://dx.doi.org/10.1016/s1631-0721(02)01548-6.

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Zhang, Yale, et J. Fraser Forbes. « Performance Analysis of Perturbation-Based Methods for Real-Time Optimization ». Canadian Journal of Chemical Engineering 84, n^o 2 (19 mai 2008) : 209–18. http://dx.doi.org/10.1002/cjce.5450840208.

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Li, Lan, Yong Hui He et Bo Wang. « Comparison of Methods of Maximum Power Point Tracking of Photovoltaic Cells ». Applied Mechanics and Materials 380-384 (août 2013) : 3362–65. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3362.

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According to engineering mathematics model of solar photovoltaic cells, a simulation model of photovoltaic cells was established in Matlab. In view of problem that it is difficult to get higher tracking accuracy and response speed by use of perturbation and observation method which applied fixed perturbation step, the paper proposed an improved perturbation and observation method based on variable step. Through simulating photovoltaic cells control system, simulation curves of two kinds of methods of maximum power point tracking were compared. The simulation results show that the photovoltaic cells control system can track maximum power point more quickly and has better stability at the maximum power point by use of the improved perturbation and observation method.

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Cha, Philip D., et Austin Shin. « Perturbation Methods for the Eigencharacteristics of Symmetric and Asymmetric Systems ». Shock and Vibration 2018 (17 octobre 2018) : 1–25. http://dx.doi.org/10.1155/2018/8609138.

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Dynamic analysis for a vibratory system typically begins with an evaluation of its eigencharacteristics. However, when design changes are introduced, the eigensolutions of the system change and thus must be recomputed. In this paper, three different methods based on the eigenvalue perturbation theory are introduced to analyze the effects of modifications without performing a potentially time-consuming and costly reanalysis. They will be referred to as the straightforward perturbation method, the incremental perturbation method, and the triple product method. In the straightforward perturbation method, the eigenvalue perturbation theory is used to formulate a first-order and a second-order approximation of the eigensolutions of symmetric and asymmetric systems. In the incremental perturbation method, the straightforward approach is extended to analyze systems with large perturbations using an iterative scheme. Finally, in the triple product method, the accuracy of the approximate eigenvalues is significantly improved by exploiting the orthogonality conditions of the perturbed eigenvectors. All three methods require only the eigensolutions of the nominal or unperturbed system, and in application, they involve simple matrix multiplications. Numerical experiments show that the proposed methods achieve accurate results for systems with and without damping and for systems with symmetric and asymmetric system matrices.

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Thèses sur le sujet "Perturbation-Based methods"

Khabir, Mohmed Hassan Mohmed. « Numerical singular perturbation approaches based on spline approximation methods for solving problems in computational finance ». Thesis, University of the Western Cape, 2011. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_7416_1320395978.

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Options are a special type of derivative securities because their values are derived from the value of some underlying security. Most options can be grouped into either of the two categories: European options which can be exercised only on the expiration date, and American options which can be exercised on or before the expiration date. American options are much harder to deal with than European ones. The reason being the optimal exercise policy of these options which led to free boundary problems. Ever since the seminal work of Black and Scholes [J. Pol. Econ. 81(3) (1973), 637-659], the differential equation approach in pricing options has attracted many researchers. Recently, numerical singular perturbation techniques have been used extensively for solving many differential equation models of sciences and engineering. In this thesis, we explore some of those methods which are based on spline approximations to solve the option pricing problems. We show a systematic construction and analysis of these methods to solve some European option problems and then extend the approach to solve problems of pricing American options as well as some exotic options. Proposed methods are analyzed for stability and convergence. Thorough numerical results are presented and compared with those seen in the literature.

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Fukasaku, Kotaro. « Explorative study for stochastic failure analysis of a roughened bi-material interface : implementation of the size sensitivity based perturbation method ». Thesis, Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41114.

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In our age in which the use of electronic devices is expanding all over the world, their reliability and miniaturization have become very crucial. The thesis is based on the study of one of the most frequent failure mechanisms in semiconductor packages, the delamination of interface or the separation of two bonded materials, in order to improve their adhesion and a fortiori the reliability of microelectronic devices. It focuses on the metal (-oxide) / polymer interfaces because they cover 95% of all existing interfaces. Since several years, research activities at mesoscopic scale (1-10µm) have proved that the more roughened the surface of the interface, i.e., presenting sharp asperities, the better the adhesion between these two materials. Because roughness exhibits extremely complex shapes, it is difficult to find a description that can be used for reliability analysis of interfaces. In order to investigate quantitatively the effect of roughness variation on adhesion properties, studies have been carried out involving analytical fracture mechanics; then numerical studies were conducted with Finite Element Analysis. Both were done in a deterministic way by assuming an ideal profile which is repeated periodically. With the development of statistical and stochastic roughness representation on the one hand, and with the emergence of probabilistic fracture mechanics on the other, the present work adds a stochastic framework to the previous studies. In fact, one of the Stochastic Finite Element Methods, the Perturbation method is chosen for implementation, because it can investigate the effect of the geometric variations on the mechanical response such as displacement field. In addition, it can carry out at once what traditional Finite Element Analysis does with numerous simulations which require changing geometric parameters each time. This method is developed analytically, then numerically by implementing a module in a Finite Element package MSc. Marc/Mentat. In order to get acquainted and to validate the implementation, the Perturbation method is applied analytically and numerically to the 3 point bending test on a beam problem, because the input of the Perturbation method in terms of roughness parameters is still being studied. The capabilities and limitations of the implementation are outlined. Finally, recommendations for using the implementation and for furture work on roughness representation are discussed.

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Graf, Daniel [Verfasser], et Christian [Akademischer Betreuer] Ochsenfeld. « Development of efficient electronic-structure methods based on the adiabatic-connection fluctuation-dissipation theorem and Møller–Plesset perturbation theory / Daniel Graf ; Betreuer : Christian Ochsenfeld ». München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2021. http://d-nb.info/123217629X/34.

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Jue, Stephen Gregory. « Characterizing Neurotransmitter Receptor Activation with a Perturbation Based Decomposition Method ». DigitalCommons@CalPoly, 2016. https://digitalcommons.calpoly.edu/theses/1631.

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The characterization of postsynaptic potentials, in terms of neurotransmitter receptor activation, is of clinical significance because information associated with receptor activation can be used in the diagnosis and study of neurological disorders. Single-unit recordings provide a method of measuring postsynaptic potentials in neurons using a microelectrode system, but yield no detailed information regarding the neurotransmitter receptors that contribute to the potential. To determine the types of neurotransmitter receptors that result in a compound postsynaptic potential from a microelectrode reading, decomposition of the potential is necessary. In this work, a perturbation-based decomposition method developed by R. Szlavik is evaluated for this application, and compared to a generalized Fourier series approach. The resultant estimator is valid for decomposition of multiple-receptor compound postsynaptic potentials as well as single-receptor compound postsynaptic potentials. The estimator also yields a satisfactory decomposition of experimental postsynaptic potential data found in the literature.

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Ben, Gamra Siwar. « Contribution à la mise en place de réseaux profonds pour l'étude de tableaux par le biais de l'explicabilité : Application au style Tenebrisme ("clair-obscur") ». Electronic Thesis or Diss., Littoral, 2023. http://www.theses.fr/2023DUNK0695.

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La détection de visages à partir des images picturales du style clair-obscur suscite un intérêt croissant chez les historiens de l'art et les chercheurs afin d'estimer l'emplacement de l'illuminant et ainsi répondre à plusieurs questions techniques. L'apprentissage profond suscite un intérêt croissant en raison de ses excellentes performances. Une optimisation du Réseau "Faster Region-based Convolutional Neural Network" a démontré sa capacité à relever efficacement les défis et à fournir des résultats prometteurs en matière de détection de visages à partir des images clai-obscur. Cependant, ces réseaux sont caractérisés comme des "boites noires" en raison de la complexité inhérentes et de la non-linéarité de leurs architectures. Pour aborder ces problèmes, l'explicabilité devient un domaine de recherche actif pour comprendre les modèles profonds. Ainsi, nous proposons une nouvelle méthode d'explicabilité itérative basée sur des perturbations guidées pour expliquer les prédictions
Face detection from Tenebrism paintings is of growing interest to art historians and researchers in order to estimate the illuminant location, and thereby answer several technical questions. Deep learning is gaining increasing interest due to is high performance capabilities. An optimization of Faster Region based Convolutional Neural Network has demonstrated its ability to effectively address challenges and deliver promising face detection results from Tenebrism paintings. However, deep neural networks are often characterized as "black box" because of the inherent complexity and non-linearity of their architectures. To tackle these issues, eXplainable Artificial Intelligence (XAI) is becoming an active researcj area to understand deep models. So, we propose a novel iterative XAI method based on guided perturbations to explain model's application

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Al, Hosani Mohamed. « Transient and Distributed Algorithms to Improve Islanding Detection Capability of Inverter Based Distributed Generation ». Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6235.

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Recently, a lot of research work has been dedicated toward enhancing performance, reliability and integrity of distributed energy resources that are integrated into distribution networks. The problem of islanding detection and islanding prevention (i.e. anti-islanding) has stimulated a lot of research due to its role in severely compromising the safety of working personnel and resulting in equipment damages. Various Islanding Detection Methods (IDMs) have been developed within the last ten years in anticipation of the tremendous increase in the penetration of Distributed Generation (DG) in distribution system. This work proposes new IDMs that rely on transient and distributed behaviors to improve integrity and performance of DGs while maintaining multi-DG islanding detection capability. In this thesis, the following questions have been addressed: How to utilize the transient behavior arising from an islanding condition to improve detectability and robust performance of IDMs in a distributive manner? How to reduce the negative stability impact of the well-known Sandia Frequency Shift (SFS) IDM while maintaining its islanding detection capability? How to incorporate the perturbations provided by each of DGs in such a way that the negative interference of different IDMs is minimized without the need of any type of communication among the different DGs? It is shown that the proposed techniques are local, scalable and robust against different loading conditions and topology changes. Also, the proposed techniques can successfully distinguish an islanding condition from other disturbances that may occur in power system networks. This work improves the efficiency, reliability and safety of integrated DGs, which presents a necessary advance toward making electric power grids a smart grid.
Ph.D.
Doctorate
Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering

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Dixit, Akash. « Damage modeling and damage detection for structures using a perturbation method ». Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43575.

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This thesis is about using structural-dynamics based methods to address the existing challenges in the field of Structural Health Monitoring (SHM). Particularly, new structural-dynamics based methods are presented, to model areas of damage, to do damage diagnosis and to estimate and predict the sensitivity of structural vibration properties like natural frequencies to the presence of damage. Towards these objectives, a general analytical procedure, which yields nth-order expressions governing mode shapes and natural frequencies and for damaged elastic structures such as rods, beams, plates and shells of any shape is presented. Features of the procedure include the following: 1. Rather than modeling the damage as a fictitious elastic element or localized or global change in constitutive properties, it is modeled in a mathematically rigorous manner as a geometric discontinuity. 2. The inertia effect (kinetic energy), which, unlike the stiffness effect (strain energy), of the damage has been neglected by researchers, is included in it. 3. The framework is generic and is applicable to wide variety of engineering structures of different shapes with arbitrary boundary conditions which constitute self adjoint systems and also to a wide variety of damage profiles and even multiple areas of damage. To illustrate the ability of the procedure to effectively model the damage, it is applied to beams using Euler-Bernoulli and Timoshenko theories and to plates using Kirchhoff's theory, supported on different types of boundary conditions. Analytical results are compared with experiments using piezoelectric actuators and non-contact Laser-Doppler Vibrometer sensors. Next, the step of damage diagnosis is approached. Damage diagnosis is done using two methodologies. One, the modes and natural frequencies that are determined are used to formulate analytical expressions for a strain energy based damage index. Two, a new damage detection parameter are identified. Assuming the damaged structure to be a linear system, the response is expressed as the summation of the responses of the corresponding undamaged structure and the response (negative response) of the damage alone. If the second part of the response is isolated, it forms what can be regarded as the damage signature. The damage signature gives a clear indication of the damage. In this thesis, the existence of the damage signature is investigated when the damaged structure is excited at one of its natural frequencies and therefore it is called ``partial mode contribution". The second damage detection method is based on this new physical parameter as determined using the partial mode contribution. The physical reasoning is verified analytically, thereupon it is verified using finite element models and experiments. The limits of damage size that can be determined using the method are also investigated. There is no requirement of having a baseline data with this damage detection method. Since the partial mode contribution is a local parameter, it is thus very sensitive to the presence of damage. The parameter is also shown to be not affected by noise in the detection ambience.

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Wang, Yiwei. « Développement de stratégies de maintenance structurales prédictives pour aéronefs utilisant le pronostic à base de modèles ». Thesis, Toulouse, INSA, 2017. http://www.theses.fr/2017ISAT0005/document.

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La maintenance aéronautique est fortement régulée, notamment à travers l’établissement d’un planning de maintenance obligatoire, permettant de garantir la sureté structurale. La fréquence des arrêts en maintenance est déterminée de manière très conservative en vue d’assurer les exigences de fiabilité. Développer des stratégies de maintenance moins conservatives et plus efficaces peut alors représenter une voie pour une nouvelle croissance des compagnies aériennes. Les systèmes de monitoring embarqué de structures, sont progressivement introduits dans l’industrie aéronautique. Ces développements pourraient alors permettre de nouvelles stratégies de maintenance structurale basées sur la prévision de l’état de santé de chaque élément structural, plutôt que basée sur une maintenance programmée, tel qu’implémentée actuellement. Dans ce cadre général, ce travail se concentre sur le suivi par un système embarqué de la propagation de fissures de fatigue dans les panneaux de fuselage. Une nouvelle méthode de prévision des fissures basée sur des modèles de propagation est développée, qui permet de filtrer le bruit des mesures du système embarqué, identifier la taille actuelle de la fissure et prédire son évolution future et par conséquent la fiabilité des panneaux. Cette approche prédictive est intégrée dans le processus de maintenance structurale aéronautique et deux types de maintenances prédictives sont proposés. L’étude numérique montre que ces stratégies de maintenance prédictive peuvent réduire de manière significative les coûts de maintenance en réduisant le nombre d’arrêts en maintenance et le nombre de réparations inutiles
Aircraft maintenance represents a major economic cost for the aviation industry. Traditionally, the aircraft maintenance is highly regulated based on fixed schedules (thus called scheduled maintenance) in order to ensure safety. The frequency of scheduled maintenance is designed to be very conservative to maintain a desirable level of reliability. Developing efficient maintenance can be an important way for airlines to allow a new profit growth. With the development of sensor technology, structural health monitoring (SHM) system, which employ a sensor network sealing inside aircraft structures to monitor the damage state, are gradually being introduced in the aviation industry. Once it is possible to monitor the structure damage state automatically and continuously by SHM systems, it enables to plan the maintenance activities according to the actual or predicted health state of the aircraft rather than a fixed schedule. This work focus on the fatigue crack propagation in the fuselage panels. The SHM system is assumed to be employed. A model-based prognostics method is developed, which enables to filter the noise of SHM data to estimate the crack size, and to predict the future health state of the panels. This predictive information is integrated into the maintenance decision-making and two types of predictive maintenance are developed. The numerical study shows that the predictive maintenance significantly reduces the maintenance cost by reducing the number of maintenance stop and the repaired panels

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Abid, Fatma. « Contribution à la robustesse et à l'optimisation fiabiliste des structures Uncertainty of shape memory alloy micro-actuator using generalized polynomial chaos methodUncertainty of shape memory alloy micro-actuator using generalized polynomial chaos method Numerical modeling of shape memory alloy problem in presence of perturbation : application to Cu-Al-Zn-Mn specimen An approach for the reliability-based design optimization of shape memory alloy structure Surrogate models for uncertainty analysis of micro-actuator ». Thesis, Normandie, 2019. http://www.theses.fr/2019NORMIR24.

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La conception des ouvrages économiques a suscité de nombreux progrès dans les domaines de la modélisation et de l’optimisation, permettant l’analyse de structures de plus en plus complexes. Cependant, les conceptions optimisées sans considérer les incertitudes des paramètres, peuvent ne pas respecter certains critères de fiabilité. Pour assurer le bon fonctionnement de la structure, il est important de prendre en considération l’incertitude dès la phase de conception. Il existe plusieurs théories dans la littérature pour traiter les incertitudes. La théorie de la fiabilité des structures consiste à définir la probabilité de défaillance d’une structure par la probabilité que les conditions de bon fonctionnement ne soient pas respectées. On appelle cette étude l’analyse de la fiabilité. L’intégration de l’analyse de fiabilité dans les problèmes d’optimisation constitue une nouvelle discipline introduisant des critères de fiabilité dans la recherche de la configuration optimale des structures, c’est le domaine de l’optimisation fiabiliste (RBDO). Cette méthodologie de RBDO vise donc à considérer la propagation des incertitudes dans les performances mécaniques en s’appuyant sur une modélisation probabiliste des fluctuations des paramètres d’entrée. Dans ce cadre, ce travail de thèse porte sur l’analyse robuste et l’optimisation fiabiliste des problèmes mécaniques complexes. Il est important de tenir compte des paramètres incertains du système pour assurer une conception robuste. L’objectif de la méthode RBDO est de concevoir une structure afin d’établir un bon compromis entre le coût et l’assurance de fiabilité. Par conséquent, plusieurs méthodes, telles que la méthode hybride et la méthode optimum safety factor, ont été développées pour atteindre cet objectif. Pour remédier à la complexité des problèmes mécaniques complexes comportant des paramètres incertains, des méthodologies spécifiques à cette problématique, tel que les méthodes de méta-modélisation, ont été développées afin de bâtir un modèle de substitution mécanique, qui satisfait en même temps l’efficacité et la précision du modèle
The design of economic system leads to many advances in the fields of modeling and optimization, allowing the analysis of structures more and more complex. However, optimized designs can suffer from uncertain parameters that may not meet certain reliability criteria. To ensure the proper functioning of the structure, it is important to consider uncertainty study is called the reliability analysis. The integration of reliability analysis in optimization problems is a new discipline introducing reliability criteria in the search for the optimal configuration of structures, this is the domain of reliability optimization (RBDO). This RBDO methodology aims to consider the propagation of uncertainties in the mechanical performance by relying on a probabilistic modeling of input parameter fluctuations. In this context, this thesis focuses on a robust analysis and a reliability optimization of complex mechanical problems. It is important to consider the uncertain parameters of the system to ensure a robust design. The objective of the RBDO method is to design a structure in order to establish a good compromise between the cost and the reliability assurance. As a result, several methods, such as the hybrid method and the optimum safety factor method, have been developed to achieve this goal. To address the complexity of complex mechanical problems with uncertain parameters, methodologies specific to this issue, such as meta-modeling methods, have been developed to build a mechanical substitution model, which at the same time satisfies the efficiency and the precision of the model

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Wu, Chia-Pin, et 吳佳斌. « Using Singular Perturbation Methods in Observer-based Controller Design ». Thesis, 2012. http://ndltd.ncl.edu.tw/handle/88637893484414157491.

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博士
國立臺灣科技大學
電機工程系
100
The thesis is mainly to design the controller by applying the theory of singular perturbation. First of all, using the singular perturbation technique to design the output feedback controller of mechanic systems, it is similar to the design of a proportional-derivative control law. We can precede the speed control by only measuring the displacement. The controller algorithm is the rule of low-order dynamic output feedback control. It is simple and easily accomplished. Besides, when the mechanical system contains uncertain items, this thesis presents robust stability of the closed-loop system. It also offers the analysis of Lyapunov theory by solving a Riccati algebra equation and a linear matrix inequality. Furthermore, for the mismatched parameter uncertainties and matched nonlinear perturbations in a linear MIMO system, the thesis proposes a disturbance-observer based controller in which the input disturbance can be effectively estimated by using a high-gain integration observer. Finally, it is verified the practicability by numerical examples.

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Chapitres de livres sur le sujet "Perturbation-Based methods"

Moura, Ana S., et M. Natália D. S. Cordeiro. « Got to Write a Classic : Classical and Perturbation-Based QSAR Methods, Machine Learning, and the Monitoring of Nanoparticle Ecotoxicity ». Dans Methods in Pharmacology and Toxicology, 195–213. New York, NY : Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0150-1_9.

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Nakatani, Naoki, Jia-Jia Zheng et Shigeyoshi Sakaki. « Approach of Electronic Structure Calculations to Crystal ». Dans The Materials Research Society Series, 209–55. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0260-6_11.

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AbstractNowadays, the importance of molecular crystals and solids with regular structures is increasing in both basic chemistry and applied fields. However, theoretical studies of those systems based on electronic structure theories have been limited. Although density functional theory (DFT) calculations using generalized gradient approximation type functional under periodic boundary condition is effective for such theoretical studies, we need some improvements for calculating the dispersion interaction and the excited state of crystals. Accordingly, in this chapter, two methods for calculating the electronic structures of molecular crystals are discussed: cluster-model/periodic-model (CM/PM)-combined method and quantum mechanics/periodic-molecular mechanics (QM/periodic-MM) method. In the CM/PM-combined method, an infinite crystal system is calculated by the DFT method under periodic boundary condition, and important moieties, which are represented by CMs, are calculated by either DFT method with hybrid-type functionals or wave function theories such as the Møller–Plesset second-order perturbation theory (MP2), spin-component-scaled-MP2, and coupled-cluster singles and doubles theory with perturbative triples (CCSD(T)). This method is useful for gas adsorption into crystals such as metal–organic frameworks. In the QM/periodic-MM method, an important moiety is calculated using a QM method such as the DFT method with hybrid-type functionals and wave function theories, where the effects of the crystal are incorporated into the QM calculation via the periodic MM method using a classical force field. This method is useful for theoretical studies of excited states and chemical reactions. The applications of these methods in the following processes are described in this chapter: adsorption of gas molecules on metal–organic frameworks, chemical reactions in crystals, and luminescence of the crystals of transition metal complexes. To the best of our knowledge, the theoretical calculations conducted in this chapter show one of the successful approaches of electronic structure theories to molecular crystals, because of the reasonable and practical approximations.

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Romanazzi, Mario. « Perturbation Properties of Depth Regions ». Dans Statistical Data Analysis Based on the L1-Norm and Related Methods, 301–12. Basel : Birkhäuser Basel, 2002. http://dx.doi.org/10.1007/978-3-0348-8201-9_25.

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Wu, Haoze, Aleksandar Zeljić, Guy Katz et Clark Barrett. « Efficient Neural Network Analysis with Sum-of-Infeasibilities ». Dans Tools and Algorithms for the Construction and Analysis of Systems, 143–63. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99524-9_8.

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AbstractInspired by sum-of-infeasibilities methods in convex optimization, we propose a novel procedure for analyzing verification queries on neural networks with piecewise-linear activation functions. Given a convex relaxation which over-approximates the non-convex activation functions, we encode the violations of activation functions as a cost function and optimize it with respect to the convex relaxation. The cost function, referred to as the Sum-of-Infeasibilities (SoI), is designed so that its minimum is zero and achieved only if all the activation functions are satisfied. We propose a stochastic procedure, , to efficiently minimize the SoI. An extension to a canonical case-analysis-based complete search procedure can be achieved by replacing the convex procedure executed at each search state with . Extending the complete search with achieves multiple simultaneous goals: 1) it guides the search towards a counter-example; 2) it enables more informed branching decisions; and 3) it creates additional opportunities for bound derivation. An extensive evaluation across different benchmarks and solvers demonstrates the benefit of the proposed techniques. In particular, we demonstrate that SoI significantly improves the performance of an existing complete search procedure. Moreover, the SoI-based implementation outperforms other state-of-the-art complete verifiers. We also show that our technique can efficiently improve upon the perturbation bound derived by a recent adversarial attack algorithm.

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Huynh, T. V. « A Perturbation Technique Based on the Integral Variation Method ». Dans Stability of the Solar System and Its Minor Natural and Artificial Bodies, 390. Dordrecht : Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5398-7_46.

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Yang, Xinyue, Hai Huang et Xingquan Zuo. « Random Mask Perturbation Based Explainable Method of Graph Neural Networks ». Dans Advances in Knowledge Discovery and Data Mining, 17–29. Singapore : Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2259-4_2.

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Vyatkin, Sergey, Alexander Romanyuk, Sergey Pavlov et Oksana Romanyuk. « Identification of Persons Using Stereo Image Pairs and Perturbation Functions ». Dans Biometric Identification Technologies Based on Modern Data Mining Methods, 119–33. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48378-4_8.

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Mori, M., et O. Ukai. « Design Sensitivity Analysis Based on Successive Perturbation Method and its Application ». Dans Computational Mechanics ’88, 1773–74. Berlin, Heidelberg : Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-61381-4_465.

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Shi, Ting C., Zhan F. Ying, Tian Y. Yuan, Yun J. Cheng et Jia X. Lin. « A Maximum Power Point Tracking Strategy Based on Perturbation Observation Method ». Dans Lecture Notes in Mechanical Engineering, 4447–56. Singapore : Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8048-2_306.

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Yang, Yong, Kan Tian et Zhengrong Chen. « A Robust Face Recognition Method Based on AdaBoost, EHMM and Sample Perturbation ». Dans Rough Sets and Knowledge Technology, 428–33. Berlin, Heidelberg : Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24425-4_56.

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Actes de conférences sur le sujet "Perturbation-Based methods"

Zhao, Zhao, et Roberto Leidhold. « Speed as Perturbation in Anisotropy Based Sensorless Control Methods ». Dans 2023 11th International Conference on Power Electronics and ECCE Asia (ICPE 2023 - ECCE Asia). IEEE, 2023. http://dx.doi.org/10.23919/icpe2023-ecceasia54778.2023.10213792.

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Li, Marvin, Jason Wang, Jeffrey Wang et Seth Neel. « MoPe : Model Perturbation based Privacy Attacks on Language Models ». Dans Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA : Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.emnlp-main.842.

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Ding, D. Y. « Improving Perturbation Designs for Gradient-based Optimization Methods in History Matching ». Dans 12th European Conference on the Mathematics of Oil Recovery. Netherlands : EAGE Publications BV, 2010. http://dx.doi.org/10.3997/2214-4609.20144995.

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Vu, Minh N., et My T. Thai. « Limitations of Perturbation-based Explanation Methods for Temporal Graph Neural Networks ». Dans 2023 IEEE International Conference on Data Mining (ICDM). IEEE, 2023. http://dx.doi.org/10.1109/icdm58522.2023.00071.

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Chen, Lichang, Jiuhai Chen, Heng Huang et Minhao Cheng. « PTP : Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer ». Dans Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA : Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.emnlp-main.833.

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Yang, Xixi, Li Fu, Yafeng Deng, Yuansheng Liu, Dongsheng Cao et Xiangxiang Zeng. « GPMO : Gradient Perturbation-Based Contrastive Learning for Molecule Optimization ». Dans Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California : International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/549.

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Optimizing molecules with desired properties is a crucial step in de novo drug design. While translation-based methods have achieved initial success, they continue to face the challenge of the “exposure bias” problem. The challenge of preventing the “exposure bias” problem of molecule optimization lies in the need for both positive and negative molecules of contrastive learning. That is because generating positive molecules through data augmentation requires domain-specific knowledge, and randomly sampled negative molecules are easily distinguished from the real molecules. Hence, in this work, we propose a molecule optimization method called GPMO, which leverages a gradient perturbation-based contrastive learning method to prevent the “exposure bias” problem in translation-based molecule optimization. With the assistance of positive and negative molecules, GPMO is able to effectively handle both real and artificial molecules. GPMO is a molecule optimization method that is conditioned on matched molecule pairs for drug discovery. Our empirical studies show that GPMO outperforms the state-of-the- art molecule optimization methods. Furthermore, the negative and positive perturbations improve the robustness of GPMO.

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Pokusiński, Bartłomiej M., et Marcin M. Kamiński. « On influence of the response functions on the diagrid and orthogonal grillages reliability by the stochastic iterative perturbation-based finite element method ». Dans COMPUTER METHODS IN MECHANICS (CMM2017) : Proceedings of the 22nd International Conference on Computer Methods in Mechanics. Author(s), 2018. http://dx.doi.org/10.1063/1.5019164.

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Yu, Chaojian, Bo Han, Mingming Gong, Li Shen, Shiming Ge, Du Bo et Tongliang Liu. « Robust Weight Perturbation for Adversarial Training ». Dans Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California : International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/512.

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Overfitting widely exists in adversarial robust training of deep networks. An effective remedy is adversarial weight perturbation, which injects the worst-case weight perturbation during network training by maximizing the classification loss on adversarial examples. Adversarial weight perturbation helps reduce the robust generalization gap; however, it also undermines the robustness improvement. A criterion that regulates the weight perturbation is therefore crucial for adversarial training. In this paper, we propose such a criterion, namely Loss Stationary Condition (LSC) for constrained perturbation. With LSC, we find that it is essential to conduct weight perturbation on adversarial data with small classification loss to eliminate robust overfitting. Weight perturbation on adversarial data with large classification loss is not necessary and may even lead to poor robustness. Based on these observations, we propose a robust perturbation strategy to constrain the extent of weight perturbation. The perturbation strategy prevents deep networks from overfitting while avoiding the side effect of excessive weight perturbation, significantly improving the robustness of adversarial training. Extensive experiments demonstrate the superiority of the proposed method over the state-of-the-art adversarial training methods.

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Rahman, T., E. L. Jansen et P. Tiso. « A Finite Element Based Perturbation Method for Nonlinear Free Vibration of Composite Cylindrical Shells ». Dans ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-11302.

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In this paper a finite element based perturbation approach for nonlinear vibrations is presented that is applicable to shell structures with an arbitrary geometry. The approach is based on a perturbation method to approximate the frequency-amplitude relation in the nonlinear vibration analysis of general structures with an arbitrary geometry. The method is formulated using a functional notation, and is subsequently converted to a finite element notation. After the determination of the linear natural frequency and corresponding vibration mode, the perturbation approach yields the initial curvature of the frequency-amplitude relation with a modest additional computational cost. The perturbation approach has been implemented in a general purpose finite element code and applied in the finite element analysis of the nonlinear vibration behavior of composite cylindrical shells using a curved shell element. The finite element implementation of the approach for composite shells is described. Results for composite cylindrical shells are presented and compared with results obtained via semi-analytical methods published earlier by the second author.

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Geer, James, et John Fillo. « Finite Difference Schemes for Diffusion Problems Based on a Hybrid Perturbation Galerkin Method ». Dans ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-16162.

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A new technique for the development of finite difference schemes for diffusion equations is presented. The model equations are the one space variable advection diffusion equation and the two space variable diffusion equation, each with Dirichlet boundary conditions. A two-step hybrid technique, which combines perturbation methods, based on the parameter ρ = Δt / (Δx)2, with the Galerkin method, provides a systematic way to develop new finite difference methods, referred to as hybrid equations. The main contributions of this paper include: 1) recovery of classical explicit or implicit finite difference schemes using only the perturbation terms; 2) development of new finite difference schemes, referred to as hybrid equations, which have better stability properties than the classical finite difference equations, permitting the use of larger values of the parameter ρ; and 3) higher order accurate methods, with either O((Δx)4) or O((Δx)6) truncation error, formed by convex linear combinations of the classical and hybrid equations. The solution of the hybrid finite difference equations requires only a tridiagonal equation solver and, hence, does not lead to excessive computational effort.

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