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IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS)

作者： Ewelina Bartuzi Mateusz Trokielewicz Institute of Control and Computation Engineering Warsaw University of Technology 00665 Warsaw Poland

ISBN: (数字)9781728115221

ISBN: (纸本)9781728115238

Robust segmentation of thermal hand images, a trivial task in controlled environments, can be difficult for unconstrained acquisition with a thermal camera, when the temperature of the object differs little from this of a background. This paper implements a method for segmenting hand images collected in the thermal spectrum involving a pre-trained, off-the-shelf data-driven model, fine-tuned with multiple databases of thermal hand images and corresponding, manually annotated ground truth masks. This allows superior performance for difficult samples, compared against conventional methods such as Otsu's thresholding and Gaussian Mixture Modeling. The segmentation accuracy for good quality samples is comparable with these traditional methods, while at the same time being more unconstrained acquisition-resistant. An improvement of up to 20% in accuracy measured by intersection over union is observed for difficult samples, such as hands that were partially colder than the background, as well as those with wristwatches and jewelry. This robust segmentation in various acquisition scenarios allows not only the correct localization of regions of interest for feature extraction, but also for extracting accurate hand geometry information. Together with the results of experiments, involving multiple training and testing scenarios on three different databases, we provide codes, model weights, and ground truth masks to ensure reproducibility and facilitate further research.

关键词： Image segmentation Databases Task analysis Cameras Measurement Feature extraction Image color analysis

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Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint

arXiv

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arXiv 2020年

作者： Amanatidis, Georgios Fusco, Federico Lazos, Philip Leonardi, Stefano Reiffenhäuser, Rebecca Department of Mathematical Sciences University of Essex United Kingdom Institute for Logic Language and Computation University of Amsterdam Netherlands Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome Italy

Constrained submodular maximization problems encompass a wide variety of applications, including personalized recommendation, team formation, and revenue maximization via viral marketing. The massive instances occurring in modern day applications can render existing algorithms prohibitively slow, while frequently, those instances are also inherently stochastic. Focusing on these challenges, we revisit the classic problem of maximizing a (possibly nonmonotone) submodular function subject to a knapsack constraint. We present a simple randomized greedy algorithm that achieves a 5.83 approximation and runs in O(n log n) time, i.e., at least a factor n faster than other state-of-the-art algorithms. The robustness of our approach allows us to further transfer it to a stochastic version of the problem. There, we obtain a 9-approximation to the best adaptive policy, which is the first constant approximation for non-monotone objectives. Experimental evaluation of our algorithms showcases their improved performance on real and synthetic data. Copyright © 2020, The Authors. All rights reserved.

关键词： Combinatorial optimization

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control Performance Assessment with Fractional Lower Order Moments

Control Performance Assessment with Fractional Lower Order M...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Kai Liu Paweł D. Domański YangQuan Chen Mechatronics Embedded Systems & Automation (MESA) Lab University of California Merced CA USA Warsaw University of Technology Institute of Control and Computation Engineering Warsaw Poland University of California Merced CA USA

ISBN: (数字)9781728159539

ISBN: (纸本)9781728159546

Non-Gaussian statistical signal processing is be-coming increasingly significant in the current complex world. However, the variance of a non-Gaussian distribution may not exist, therefore many conventional methods will be considerably weakened, meaningless or even misleading. For example, the least-squares criterion may not be robust in the non-Gaussian environment, owing to the impulsive behaviors and outliers. In the paper, the statistical measures with fractional lower order moments (FLOM) are used instead of second-order moments to assess the control performance for non-Gaussian processes. The results show that FLOM is robust against outliers for the non-Gaussian signals. In the end, Hurst exponent fitting with FLOM and multifractal detrended fluctuation analysis (MFDFA) with FLOM are applied to the real data.

关键词： Dispersion Next generation networking Information technology Gaussian distribution Fitting Time series analysis Robustness

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Robust Iterative Learning control for ladder circuits with mixed uncertainties

Robust Iterative Learning Control for ladder circuits with m...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Bartłomiej Sulikowski Krzysztof Gałkowski Eric Rogers Anton Kummert Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland School of Electronics and Computer Science University of Southampton Southampton UK Faculty of Electrical Information and Media Engineering University of Wuppertal Wuppertal Germany

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

This paper develops iterative learning control laws for a subclass of uncertain spatially interconnected systems. Model uncertainties appear both in the state (represented by the norm bounded description) and the output equation (represented by a polytopic description) of the dynamics modeled in the 2D systems setting. A particular example of an RLC ladder circuit provides an example to motivate the analysis. The first stage is to write the dynamics in 2D model form and then to apply the stability theory for a distinct class of 2D systems known as repetitive processes is used to develop the ILC law in the case of differential dynamics. This results in a design algorithm that considers the mixed uncertainties in the model and can be applied using linear matrix inequalities.

关键词： Uncertainty Mathematical model Two dimensional displays RLC circuits Interconnected systems Integrated circuit modeling Iterative learning control

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Genetic Informed Trees (GIT*): Path planning via reinforced genetic programming heuristics

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Biomimetic Intelligence and Robotics 2025年

作者： Liding Zhang Kuanqi Cai Zhenshan Bing Chaoqun Wang Alois Knoll Chair of Robotics Artificial Intelligence and Real-time Systems TUM School of Computation Information and Technology (CIT) Technical University of Munich Munich 85748 Germany Chair of Robotics and Systems Intelligence Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich Munich 80992 Germany School of Control Science and Engineering Shandong University Jinan 250100 China

Optimal path planning involves finding a feasible state sequence between a start and a goal that optimizes an objective. This process relies on heuristic functions to guide the search direction. While a robust function can improve search efficiency and solution quality, current methods often overlook available environmental data and simplify the function structure due to the complexity of information relationships. This study introduces Genetic Informed Trees (GIT*), which improves upon Effort Informed Trees (EIT*) by integrating a wider array of environmental data, such as repulsive forces from obstacles and the dynamic importance of vertices, to refine heuristic functions for better guidance. Furthermore, we integrated reinforced genetic programming (RGP), which combines genetic programming with reward system feedback to mutate genotype-generative heuristic functions for GIT*. RGP leverages a multitude of data types, thereby improving computational efficiency and solution quality within a set timeframe. Comparative analyses demonstrate that GIT* surpasses existing single-query, sampling-based planners in problems ranging from R 4 to R 16 and was tested on a real-world mobile manipulation task. A video showcasing our experimental results is available at A video showcasing our experimental results is available at https://***/URjXbc_BiYg .

关键词： Genetic algorithm Reinforced genetic programming Generative heuristics Optimal path planning

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Limitations on sharing Bell nonlocality between sequential pairs of observers

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Physical Review A 2021年第6期104卷 L060201-L060201页

作者： Shuming Cheng Lijun Liu Travis J. Baker Michael J. W. Hall The Department of Control Science and Engineering Tongji University Shanghai 201804 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai 201804 China Institute for Advanced Study Tongji University Shanghai 200092 China College of Mathematics and Computer Science Shanxi Normal University Linfen 041000 China Centre for Quantum Computation and Communication Technology (Australian Research Council) Centre for Quantum Dynamics Griffith University Brisbane QLD 4111 Australia Department of Theoretical Physics Research School of Physics Australian National University Canberra ACT 0200 Australia

We give strong analytic and numerical evidence that, under mild measurement assumptions, two qubits cannot both be recycled to generate Bell nonlocality between multiple independent observers on each side. This is surprising, as under the same assumptions it is possible to recycle just one of the qubits an arbitrarily large number of times [P. J. Brown and R. Colbeck, Phys. Rev. Lett. 125, 090401 (2020)]. We derive corresponding one-sided monogamy relations that rule out two-sided recycling for a wide range of parameters, based on a general tradeoff relation between the strengths and maximum reversibilities of qubit measurements. We also show if the assumptions are relaxed to allow sufficiently biased measurement selections, then there is a narrow range of measurement strengths that allows two-sided recycling for two observers on each side, and propose an experimental test. Our methods may be readily applied to other types of quantum correlations, such as steering and entanglement, and hence to general information protocols involving sequential measurements.

关键词： Nonlocality Quantum correlations in quantum information

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Robust actuator and sensor fault estimation for Takagi-Sugeno fuzzy systems under ellipsoidal bounding

Robust actuator and sensor fault estimation for Takagi-Sugen...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Marcin Witczak Marcin Pazera Norbert Kukurowski Teódulo Iván Bravo Cruz Didier Theilliol Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Tuxtla Gutiérrez Institute of Technology National Technological Institute of Mexico TURIX-Dynamics Diagnosis and Control Group Tuxtla Gutierrez Chiapas Mexico CRAN UMR 7039 Campus Sciences Unversite de Lorrain France

ISBN: (数字)9781728169323

ISBN: (纸本)9781728169330

The paper undertakes the problem of designing a simultaneous sensor and actuator fault estimation scheme for Takagi-Sugeno fuzzy systems. Thus, the paper starts with the development of such a fault estimation scheme capable of estimating these faults simultaneously. Apart from estimating the faults, the proposed scheme provides the so-called uncertainty intervals, which overbound an unknown state and faults. These intervals can be applied for both reliable fault diagnosis as well as assessment of the estimation quality. Indeed, the smaller the intervals the better the estimation. To settle the above problem, an assumption is imposed, which yields that the external disturbances are overbounded by an ellipsoid. This permits employing the quadratic boundedness approach both both the estimator convergence analysis as well as determination of lower and upper bounds of uncertainty intervals. Finally, the performance of the proposed approach is examined by exploiting the laboratory three-tank system. In particular, the effectiveness of the proposed scheme is tested against a set of simultaneous actuator and sensor faults, respectively.

关键词： Actuators Uncertainty Takagi-Sugeno model Estimation error Fuzzy systems Robustness

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New relaxed stability and stabilization conditions for differential linear repetitive processes ⁎

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IFAC-PapersOnLine 2020年第2期53卷 1462-1467页

作者： Robert Maniarski Wojciech Paszke Eric Rogers Marcin Boski Institute of Control and Computation Engineering University of Zielona Góra ul. Szafrana 2 65-516 Zielona Góra Poland School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ UK

The paper develops new results on the stability analysis of differential linear repetitive processes. These processes are a distinct class of two-dimensional systems that arise in the modelling of physical processes and also the existing systems theory for them can be used to effect in solving control problems for other classes of systems, including iterative learning control design. This paper uses a version of the Kalman-Yakubovich-Popov Lemma to develop relaxed conditions for the stability property in terms of linear matrix inequalities. The main result is reduced conservatism in applying tests for the stability property with an extension to control law design. A numerical example to illustrate the application of the new results is also given.

关键词： Repetitive processes stability along the pass linear matrix inequalities finite frequency domain

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Implementation of Multiple-Input Multiple-Output Dynamic Matrix control Algorithm for Fast Processes Using Field Programmable Gate Array

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IFAC-PapersOnLine 2018年第6期51卷 324-329页

作者： Wojtulewicz, Andrzej Lawryczuk, Maciej Institute of Control and Computation Engineering Warsaw University of Technology ul. Nowowiejska 15/19 Warsaw00-665 Poland

The objective of this paper is to describe an implementation of a Dynamic Matrix control (DMC) algorithm for a Field Programmable Gate Array (FPGA). The DMC algorithm is implemented in a universal version for multiple-input multiple-output dynamic processes. The results of real experiments are presented in which the DE2i-150 development board produced by Terasic with Intel Cyclone IV GX chip is used. As the controlled process a laboratory stand especially developed for this work is used, which is a dynamic system with two manipulated inputs and two controlled outputs. The implemented DMC controller is very fast, it may be used for controlling processed which need sampling periods of a millisecond order. © 2018

关键词： Field programmable gate arrays (FPGA) Codes (symbols) Feedback control Logic gates MIMO systems Model predictive control Storms Telecommunication repeaters controlled process Dynamic matrix control Dynamic matrix control algorithms Dynamic process Fast process Sampling period

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Dynamic Matrix control Algorithm Implementation on ARM Cortex-R5 MCU: Performance Analysis

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IFAC-PapersOnLine 2018年第6期51卷 330-335页

作者： Czerwiski, Kamil Lawryczuk, Maciej Institute of Control and Computation Engineering Warsaw University of Technology ul. Nowowiejska 15/19 Warsaw00-665 Poland

This paper describes implementation of the Dynamic Matrix control (DMC) algorithm using a microcontroller with the ARM Cortex R5 core. Two versions of the DMC algorithm are considered: the classical one and the simplified one. It is shown that the latter one needs much shorter calculation time, but give the same control quality. Moreover, the influence of tuning parameters of the DMC algorithm on the calculation time is studied experimentally. The obtained implementation of the DMC algorithm can be used in very fast embedded system, with short sampling periods. Results of real experiment are demonstrated for Hercules RM57L843 LaunchPad board from Texas Instruments. © 2018

关键词： Embedded systems ARM processors control theory controllers Microcontrollers Microprocessor chips Model predictive control Real time systems Calculation time Dynamic matrix control Dynamic matrix control algorithms Performance analysis Real time embedded systems Short sampling period Texas Instruments Tuning parameter

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