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Hierarchical Robust Analysis for Identified Systems in Network⁎

IFAC-PapersOnLine 2018年第25期51卷 383-389页

作者： Korniienko, A. Bombois, X. Hjalmarsson, H. Scorletti, G. Laboratoire Ampère Université de Lyon École Centrale de Lyon Ecully Cedex69134 France Automatic Control School of Electrical Engineering KTH Stockholm100 44 Sweden

This paper considers worst-case robustness analysis of a network of locally controlled uncertain systems with uncertain parameter vectors belonging to the ellipsoid sets found by identification procedures. In order to deal with computational complexity of large-scale systems, an hierarchical robustness analysis approach is adapted to these uncertain parameter vectors thus addressing the trade-off between the computation time and the conservatism of the result. © 2018

关键词： Hierarchical systems Economic and social effects Large scale systems Multi agent systems Networks (circuits) Parameter estimation Uncertainty analysis computation time Identification for control Identification procedure Multi agent Robust analysis Robustness analysis Uncertain parameters Worst case robustness

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Selection of spectrum model in estimation of Brillouin frequency shift for distributed optical fiber sensor

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OPTIK 2019年 199卷 163355-000页

作者： Xu, Zhi-niu Zhao, Li-juan Qin, Hua North China Elect Power Univ Sch Elect & Elect Engn Baoding 071003 Peoples R China Guangxi Power Grid Corp Grid Planning & Res Ctr Nanning 530000 Peoples R China

To improve real-time performance in distributed optical fiber sensor, the influence of Brillouin spectrum models on performance in estimation of Brillouin frequency shift (BFS) is systematically investigated. First, the related Brillouin spectrum models, objective functions, optimization algorithms and convergence criterion in estimation of BFS are introduced. The BFS estimation algorithms based on the Lorentzian, Gaussian, pseudo-Voigt and Voigt models are written in MATLAB. The algorithms are used to estimate BFS for numerically generated Brillouin spectra with different values of SNR (Signal to Noise Ratio) and measured Brillouin spectra with different values of pulse width and average time. The results reveal that regardless of the simplified Lorentzian and Gaussian models or more accurate pseudo-Voigt and Voigt model-based algorithms used, the estimated BFS between different algorithms is quite similar. However, the fitting error of the simplified model-based algorithms is larger than that of the more accurate model-based algorithms especially for the cases with high value of SNR. The computational burden of the former is less than that of the latter. The Voigt model-based algorithm requires the most computational effort. If the nonlinear least-square fit method is used, the selection of spectrum model has no big influence on the accuracy in the estimated BFS. Therefore, the algorithm based on simplified Lorentzian and Gaussian models should be selected in BFS estimation. Thus, not only high accuracy in BFS estimation is ensured, but also the computation time can, at best, decrease to one-tenth of the maximum value.

关键词： Distributed optical fiber sensing Brillouin frequency shift Spectrum model Accuracy computation time

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Magneto-mechanical analysis of magnetic gear pole pieces ring from analytical models for wind turbine applications

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WIND ENGINEERING 2018年第4期42卷 276-285页

作者： Desvaux, M. Multon, B. Ben Ahmed, H. Sire, S. Univ Bretagne Loire CNRS ENS Rennes SATIE Lab F-35044 Bruz France Univ Bretagne Occidentale CNRS 3744 IRDL FRE Brest France

This article deals with the structural behavior of a multi-bar system which maintains pole pieces in a concentric magnetic gear. Simplified analytic magnetic and mechanical models of the system are proposed in order to be integrated in a multi-criteria global optimization for the sizing of a magnetic gear in wind power applications. For this purpose, the reduction of the computation time is taken into account. The geometry of the support bar subsystem is defined and a Q bar structure is proposed. The magnetic study is based on Maxwell's equations and subdomain method in order to determine variable radial and tangential magnetic loads. The mechanical study is based on a multibody model with different bars stiffnesses which are determined from a one-dimensional model. Variable radial and tangential magneto-mechanical pole pieces loads (magnetic load and weight) are also considered. An example of a magnetic gear with 172 pole pieces (i.e. 6-MW wind turbine) is proposed to analyze the mechanical behavior and also the computation time.

关键词： Analytical model computation time laminated pole pieces magnetic gear magnetic load mechanical sizing multibody model support bar

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Improved Implementation of Dynamic Programming on the Example of Hybrid Electric Vehicle Control

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IFAC-PapersOnLine 2019年第5期52卷 147-152页

作者： Wilco van Harselaar Niels Schreuders Theo Hofman Stephan Rinderknecht Daimler AG Stuttgart Germany Mechanical Engineering Department Eindhoven University of Technology Eindhoven The Netherlands Institute for Mechatronic Systems Technische Universität Darmstadt Darmstadt Germany

Hybrid electric drivetrains are an example of systems that can enable discrete switching between states with very distinct continuous behavior. For the design of these drivetrains, the required computation time for optimizing the control over a driving cycle is critical. To reduce computation time, we propose two methods to improve the implementation of dynamic programming by reducing the number of grid points that computationally demanding sub-models are evaluated for. The proposed methods do not require surrogate models and can be applied to arbitrary drivetrain topologies. A case study on a parallel, a series-parallel, and a power-split hybrid drivetrain is performed, and a reduction in computation time of up to 66% is shown.

关键词： Dynamic programming optimal control complex systems computation time automotive control hybrid vehicles multi-mode

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Efficient Biochemical Pathway Prediction Using Simulated Annealing

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IFAC-PapersOnLine 2018年第19期51卷 56-57页

作者： Xu, Zhiqing Mahadevan, Radhakrishnan Department of Chemical Engineering and Applied Chemistry University of Toronto TorontoONM5S3E5 Canada Institute of Biomaterials and Biomedical Engineering University of Toronto TorontoONM5S3G9 Canada

During the past two decades, many computational tools were developed to aid novel biochemical pathway design. However, when longer pathways are to be predicted, putative reaction network with a large number of compounds will be generated after several steps of reactions. The combinatorial growth of the number of compounds makes expansion of the pathway search tree very slow and thus makes the identification of all possible pathways computationally intractable. Although methods based on chemical similarity have been developed to save computation time through reducing the number of nodes and branches in the reaction network according to their structural similarity to the target compound, the method can ignore important pathways containing compounds that are not relatively similar to the target compounds. We here report a new algorithm in our pathway prediction program AnnealPath that improves the performance of pathway prediction in terms of the ability to predict pathways where the intermediates are not similar to the final target compound. We have used a global optimization algorithm, simulated annealing, to improve the efficiency of predicting longer non-linear pathways. We were able to show that our new algorithm is more computationally efficient, generates more possible pathways and identifies a higher number of shorter pathways. © 2018

关键词： Simulated annealing Forecasting Global optimization Biochemical pathway Chemical similarity computation time computational tools computationally efficient Global optimization algorithm Reaction network Structural similarity

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Fast and accurate RCS evaluation via high-performance parallel FDTD simulation

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JOURNAL OF ENGINEERING-JOE 2019年第21期2019卷 7322-7325页

作者： Zhou, Xiao Long Wang, Xin Yu Zhang, Jian Feng You, Jian Wei China Ship Dev & Design Ctr Wuhan 430064 Hubei Peoples R China Southeast Univ Sch Informat & Sci Engn Nanjing 210096 Jiangsu Peoples R China

In this study, a fast and accurate method to predict the radar cross-section (RCS) of large-scale and complicated shape targets is proposed based on a high-performance parallel finite difference time-domain (FDTD) numerical method. To this end, several most popular parallel computation methods [including OpenMP, graphics processing unit (GPU), and message-passing interface (MPI)] are discussed first. Based on this discussion, a novel MPI-OpenMP-GPU hybrid parallel computation scheme for FDTD is developed. Moreover, the corresponding load-balance parallel configuration is discussed as well. Since this hybrid parallel scheme combines the merits of existing parallel technologies, the computation performance is remarkably improved. The results show that the computation time of the RCS simulation of a large-scale target can be reduced from 3 days to 0.8 h, that is, similar to 98.9% time saving.

关键词： application program interfaces radar cross-sections parallel algorithms finite difference time-domain analysis message passing parallel processing radar computing MPI high-performance parallel FDTD simulation parallel computation methods large-scale target RCS simulation computation time computation performance parallel technologies hybrid parallel scheme corresponding load-balance parallel configuration novel MPI-OpenMP-GPU hybrid parallel computation scheme message-passing interface high-performance parallel finite difference time-domain numerical method complicated shape targets radar cross-section time 0 8 hour to 3 0 d

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Further results on the fast computation of a class of hydro-mechanical systems

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IFAC-PapersOnLine 2018年第3期51卷 74-79页

作者： Sakai, Satoru Shinshu University NaganoWakasato4-17-1 Japan

This paper updates the fast computation method for a class of hydro-mechanical systems. First, a Casimir based simplified representation and a structure preserving nondimensional representation are introduced. Second, based on the two representations, a new Casimir based nondimensional representation is proposed. Finally, in comparison with other representations, the validity of the proposed representation is confirmed with respect to the computation time © 2018

关键词： computational efficiency Mechanics Casimir computation time Fast computation Hydro mechanical systems Nondimensional Structure preserving

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A Constrained Thrust Allocation Algorithm for Remotely Operated Vehicles

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IFAC-PapersOnLine 2018年第29期51卷 250-255页

作者： Baldini, Alessandro Fasano, Antonio Felicetti, Riccardo Freddi, Alessandro Longhi, Sauro Monteriù, Andrea Department of Information Engineering Università Politecnica delle Marche Via Brecce BiancheAncona60131 Italy Università Ca’ Foscari Venezia Italy

In this paper, the constrained thrust allocation problem is studied and solved for the class of over-actuated Remotely Operated Vehicles. In detail, we find the solution of the thrust allocation when the thrusters are affected by possible faults and, simultaneously, taking into account the thrusters’ saturation limits. The proposed thrust allocation algorithm is tested both numerically, with randomly generated input samples, and applied in simulation for the trajectory tracking of a Remotely Operated Vehicle, with real parameters and in combination with different control laws. The algorithm is compared with two commonly used approaches, that are the saturated pseudo-inverse method and the Matlab Quadratic Programming solver; both accuracy and computation time are considered in the analysis of the performances. The simulations show that the proposed algorithm performs better, in terms of computation time, w.r.t. the Matlab Quadratic Programming solver, while still retaining the optimality of the solution despite the saturation constraints; moreover, there is also an improvement in the tracking error regardless of the adopted control law. © 2018

关键词： Remotely operated vehicles Control theory Failure analysis Fault detection Fault tolerance Inverse problems MATLAB Quadratic programming Remote control Unmanned underwater vehicles computation time Fault tolerant systems Pseudo inverse method Saturation constraints Saturation limits Thrust allocation problems Thrust allocations Trajectory tracking

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Evolutionary sequential genetic search technique-based cancer classification using fuzzy rough nearest neighbour classifier

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HEALTHCARE TECHNOLOGY LETTERS 2018年第4期5卷 130-135页

作者： Meenachi, Loganathan Ramakrishnan, Srinivasan Dr Mahalingam Coll Engn & Technol Dept Informat Technol Pollachi Tamil Nadu India

Cancer is one of the deadly diseases of human life. The patient may likely to survive if the disease is diagnosed in its early stages. In this Letter, the authors propose a genetic search fuzzy rough (GSFR) feature selection algorithm, which is hybridised using the evolutionary sequential genetic search technique and fuzzy rough set to select features. The genetic operator's selection, crossover and mutation are applied to generate the subset of features from dataset. The generated subset is subjected to the evaluation with the modified dependency function of the fuzzy rough set using positive and boundary regions, which act as a fitness function. The generation and evaluation of the subset of features continue until the best subset is arrived at to develop the classification model. Selected features are applied to the different classifiers, from the classifiers fuzzy-rough nearest neighbour (FRNN) classifier, which outperforms in terms of classification accuracy and computation time. Hence, the FRNN is applied for performance analysis of existing feature selection algorithms against the proposed GSFR feature selection algorithm. The result generated from the proposed GSFR feature selection algorithm proved to be precise when compared to other feature selection algorithms.

关键词： FRNN classifier GSFR feature selection algorithm boundary regions cancer classification accuracy computation time deadly diseases evolutionary sequential genetic search technique-based cancer classification feature selection fitness function fuzzy rough nearest neighbour classifier fuzzy rough set fuzzy set theory generated subset genetic algorithms genetic operator genetic search fuzzy rough feature selection algorithm mathematical operators medical computing modified dependency function pattern classification positive regions rough set theory search problems

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Analytical expression for the integrated squared density partial derivative of a multivariate normal mixture distribution (vol 88, pg 2726, 2018)

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JOURNAL OF STATISTICAL computation AND SIMULATION 2018年第14期88卷 X-X页

作者： Tsai, M-H Department of Statistics National Taipei University New Taipei City Taiwan

This paper describes the derivation of the analytical expression for the integrated squared density partial derivative (ISDPD) in a multivariate normal mixture model. The analytical expression of the ISDPD is derived for arbitrary dimensions with partial derivative orders up to four. Although the value of the ISDPD can be obtained by using the common numerical integration via mathematical software (such as Maple, Mathematica, Matlab, etc), it suffers from the limitation of computation time when the dimension or the number of mixture components of the considered multivariate normal mixture model are large. Moreover, numerical comparison indicates the benefits of speed offered by our proposed analytical expression are far superior to the numerical integration performed by Maple. With this analytical expression, the ISDPD can apace be calculated with no assistance of numerical integration.

关键词： Integrated squared density partial derivative multivariate normal mixture model numerical integration computation time

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