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    Wyświetlanie 1-6 z 6
    Tytuł:
    Metric entropy of convex hulls in Hilbert spaces
    Autorzy:
    Li, Wenbo V.
    Linde, Werner
    Powiązania:
    https://bibliotekanauki.pl/articles/1206124.pdf
    Data publikacji:
    2000
    Wydawca:
    Polska Akademia Nauk. Instytut Matematyczny PAN
    Tematy:
    metric entropy
    convex hull
    majorizing measure
    Gaussian process
    Opis:
    Let T be a precompact subset of a Hilbert space. We estimate the metric entropy of co(T), the convex hull of T, by quantities originating in the theory of majorizing measures. In a similar way, estimates of the Gelfand width are provided. As an application we get upper bounds for the entropy of co(T), $T={t_1,t_2,...}$, $||t_j||≤a_j$, by functions of the $a_j$'s only. This partially answers a question raised by K. Ball and A. Pajor (cf. [1]). Our estimates turn out to be optimal in the case of slowly decreasing sequences $(a_j)_{j=1}^∞$.
    Źródło:
    Studia Mathematica; 2000, 139, 1; 29-45
    0039-3223
    Pojawia się w:
    Studia Mathematica
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Gaussian process dynamic modeling and backstepping sliding mode control for magnetic levitation system of maglev train
    Autorzy:
    Sun, Yougang
    Wang, Sumei
    Lu, Yang
    Xu, Junqi
    Powiązania:
    https://bibliotekanauki.pl/articles/2086959.pdf
    Data publikacji:
    2022
    Wydawca:
    Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
    Tematy:
    maglev train
    Gaussian process
    sliding mode control
    parameter perturbations
    Opis:
    The maglev trains are strongly nonlinear and open-loop unstable systems with external disturbances and parameters uncertainty. In this paper, the Gaussian process method is utilized to get the dynamic parameters, and a backstepping sliding mode controller is proposed for magnetic levitation systems (MLS) of maglev trains. That is, for a MLS of a maglev train, a nonlinear dynamic model with accurate parameters is obtained by the Gaussian process regression method, based on which a novel robust control algorithm is designed. Specifically, the MLS is divided into two sub-systems by a backstepping method. The inter virtual control inputs and the Lyapunov function are constructed in the first sub-system. For the second sub-system, the sliding mode surface is constructed to fulfil the design of the whole controller to asymptotically regulate the airgap to a desired trajectory. The stability of the proposed control method is analyzed by the Lyapunov method. Both simulation and experimental results are included to illustrate the superior performance of the presented method to cope with parameters perturbations and external disturbance.
    Źródło:
    Journal of Theoretical and Applied Mechanics; 2022, 60, 1; 49--62
    1429-2955
    Pojawia się w:
    Journal of Theoretical and Applied Mechanics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Modelling of Li-Ion battery state-of-health with Gaussian processes
    Autorzy:
    Dudek, Adrian
    Baranowski, Jerzy
    Powiązania:
    https://bibliotekanauki.pl/articles/28761940.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    lithium-ion batteries
    state of health
    Gaussian process
    diagnostics
    Opis:
    The problem of lithium-ion cells, which degrade in time on their own and while used, causes a significant decrease in total capacity and an increase in inner resistance. So, it is important to have a way to predict and simulate the remaining usability of batteries. The process and description of cell degradation are very complex and depend on various variables. Classical methods are based, on the one hand, on fitting a somewhat arbitrary parametric function to laboratory data and, on the other hand, on electrochemical modelling of the physics of degradation. Alternative solutions are machine learning ones or non-parametric ones like support-vector machines or the Gaussian process (GP), which we used in this case. Besides using the GP, our approach is based on current knowledge of how to use non-parametric approaches for modeling the electrochemical state of batteries. It also uses two different ways of dealing with GP problems, like maximum likelihood type II (ML-II) methods and the Monte Carlo Markov Chain (MCMC) sampling.
    Źródło:
    Archives of Electrical Engineering; 2023, 72, 3; 643--659
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Use of machine learning algorithm for the better prediction of SR peculiarities of WEDM of Nimonic-90 superalloy
    Autorzy:
    Singh Nain, S.
    Sai, R.
    Sihag, P.
    Vambol, S.
    Vambol, V.
    Powiązania:
    https://bibliotekanauki.pl/articles/378951.pdf
    Data publikacji:
    2019
    Wydawca:
    Stowarzyszenie Komputerowej Nauki o Materiałach i Inżynierii Powierzchni w Gliwicach
    Tematy:
    support vector machine
    Gaussian process
    artificial neural network
    WEDM
    maszyna wektorów nośnych
    proces gaussowski
    sztuczna sieć neuronowa
    Opis:
    Purpose: With the end goal to fulfil stringent structural shape of the component in aeronautics industry, machining of Nimonic-90 super alloy turns out to be exceptionally troublesome and costly by customary procedures, for example, milling, grinding, turning, etc. For that reason, the manufacture and design engineer worked on contactless machining process like EDM and WEDM. Based on previous studies, it has been observed that rare research work has been published pertaining to the use of machine learning in manufacturing. Therefore the current research work proposed the use of SVM, GP and ANN methods to evaluate the WEDM of Nimonic-90. Design/methodology/approach: The experiments have been performed on the WEDM considering five process variables. The Taguchi L 18 mixed type array is used to formulate the experimental plan. The surface roughness is checked by using surface contact profilometre. The evolutionary algorithms like SVM, GP and ANN approaches have been used to evaluate the SR of WEDM of Nimonic-90 super alloy. Findings: The entire models present the significant results for the better prediction of SR peculiarities of WEDM of Nimonic-90 superalloy. The GP PUK kernel model is dominating the entire model. Research limitations/implications: The investigation was carried for the Nimonic-90 super alloy is selected as a work material. Practical implications: The results of this study provide an opportunity to conduct contactless processing superalloy Nimonic-90. At the same time, this contactless process is much cheaper, faster and more accurate. Originality/value: An experimental work has been reported on the WEDM of Udimet-L605 and use of advance machine learning algorithm and optimization approaches like SVM, and GRA is recommended. A study on WEDM of Inconel 625 has been explored and optimized the process using Taguchi coupled with grey relational approach. The applicability of some evolutionary algorithm like random forest, M5P, and SVM also tested to evaluate the WEDM of Udimet-L605.The fuzzy- inference and BP-ANN approached is used to evaluate the WEDM process. The multi-objective optimization using ratio analysis approach has been utilized to evaluate the WEDM of high carbon & chromium steel. But this current research work proposed the use of SVM, GP and ANN methods to evaluate the WEDM of Nimonic-90.
    Źródło:
    Archives of Materials Science and Engineering; 2019, 95, 1; 12-19
    1897-2764
    Pojawia się w:
    Archives of Materials Science and Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Efficient learning variable impedance control for industrial robots
    Autorzy:
    Li, C.
    Zhang, Z.
    Xia, G.
    Xie, X.
    Zhu, Q.
    Powiązania:
    https://bibliotekanauki.pl/articles/200716.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    variable impedance control
    reinforcement learning
    efficient
    Gaussian process
    industrial robots
    impedancja
    poprawa efektywności
    wydajność
    model Gaussa
    roboty przemysłowe
    Opis:
    Compared with the robots, humans can learn to perform various contact tasks in unstructured environments by modulating arm impedance characteristics. In this article, we consider endowing this compliant ability to the industrial robots to effectively learn to perform repetitive force-sensitive tasks. Current learning impedance control methods usually suffer from inefficiency. This paper establishes an efficient variable impedance control method. To improve the learning efficiency, we employ the probabilistic Gaussian process model as the transition dynamics of the system for internal simulation, permitting long-term inference and planning in a Bayesian manner. Then, the optimal impedance regulation strategy is searched using a model-based reinforcement learning algorithm. The effectiveness and efficiency of the proposed method are verified through force control tasks using a 6-DoFs Reinovo industrial manipulator.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 2; 201-212
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fault tolerant control using Gaussian processes and model predictive control
    Autorzy:
    Yang, X.
    Maciejowski, J. M.
    Powiązania:
    https://bibliotekanauki.pl/articles/330117.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    fault tolerant control
    Gaussian process
    model predictive control
    aircraft control
    probabilistic modelling
    sterowanie tolerujące uszkodzenia
    proces gaussowski
    sterowanie predykcyjne
    sterowanie samolotem
    modelowanie probabilistyczne
    Opis:
    Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2015, 25, 1; 133-148
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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