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Wyniki wyszukiwania dla: ROBUST ADAPTIVE
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublikacjaThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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Effectiveness of the robust PSS design
PublikacjaThe paper discusses optimal PSS of synchronous generator synthesis. The optimal controller is an Hinf controller, what means that minimises Hinf norm of transfer function between the exogenous signals such as reference inputs and disturbances, and the error signals which are to be minimised to meet the control objective. The dynamic properties of the plant are shaped by choosing appropriate weighting function applied to the plant...
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On robust FSO network dimensioning
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Optimised Robust Placement of Hard Quality Sensors for Robust Monitoring of Quality in Drinking Water Distribution Systems
PublikacjaA problem of optimised robust placement of the hard quality sensors in Drinking Water Distribution Systems under several water demand scenarios for robust quality monitoring is formulated. Numerical algorithms to solve the problem are derived. The optimality is meant as achieving at the same time a desired trade off between the sensor capital and maintenance costs and resulting robust estimation accuracy of the monitoring algorithm...
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Towards Robust Identification of Nonstationary Systems
PublikacjaThe article proposes a fast, two-stage method for the identification of nonstationary systems. The method uses iterative reweighting to robustify the identification process against the outliers in the measurement noise and against the numerical errors that may occur at the first stage of identification. We also propose an adaptive algorithm to optimize the values of the hyperparameters that are crucial for this new method.
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A robust detector for distorted music staves
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Identification of models and signals robust to occasional outliers
PublikacjaIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Identification of models and signals robust to occasional outliers
PublikacjaIn this paper estimation algorithms derived in the sense of the least sum of absolute errors are considered for the purpose of identification of models and signals. In particular, off-line and approximate on-line estimation schemes discussed in the work are aimed at both assessing the coefficients of discrete-time stationary models and tracking the evolution of time-variant characteristics of monitored signals. What is interesting,...
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Robust H- optimal synthesis of FDI systems
PublikacjaDetekcję błędów występujących w nadzorowanym obiekcie dynamicznym, stanowią-cą podstawę decyzji diagnostycznych, oprzeć można na analizie wektorów resz-towych, generowanych w układzie zawierającym odpowiednio zaprojektowany od-porny estymator stanu danego obiektu. Rozważano tylko zewętrzny aspekt syn-tezy generatora reszt optymalnych ze względu na normę tej przestrzeni H : toznaczy problem odprzęgania wektora resztowego od niemierzalnych...
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Toward Robust Pedestrian Detection With Data Augmentation
PublikacjaIn this article, the problem of creating a safe pedestrian detection model that can operate in the real world is tackled. While recent advances have led to significantly improved detection accuracy on various benchmarks, existing deep learning models are vulnerable to invisible to the human eye changes in the input image which raises concerns about its safety. A popular and simple technique for improving robustness is using data...
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An optimization model for robust FSO network dimensioning
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Robust identification of quadrocopter model for control purposes
PublikacjaThe paper addresses a problem of quadrotor unmanned aerial vehicle (so-called X4-flyer or quadrocopter) utility model identification for control design purposes. To that goal the quadrotor model is assumed to be composed of two abstracted subsystems, namely a rigid body (plant) and four motors equipped with blades (actuators). The model of the former is acquired based on a well-established dynamic equations of motion while the...
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Non-Adaptive Rotor Speed Estimation of Induction Machine in an Adaptive Full-Order Observer
PublikacjaIn the sensorless control system of an induction machine, the rotor speed value is not measured but reconstructed by an observer structure. The rotor speed value can be reconstructed by the classical adaptive law with the integrator. The second approach, which is the main contribution of this paper, is the non-adaptive structure without an integrator. The proposed method of the rotor speed reconstruction is based on an algebraic...
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A Framework for Adaptive and Integrated Classification
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Adaptive inertial shock-absorber
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Adaptive resolution simulation of liquid para-hydrogen: testing the robustness of the quantum-classical adaptive coupling
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Robust algorithm for active feedback control of narrowband noise
PublikacjaThe problem of active control of narrowband acoustic noise is considered. It is shown that the proposed earlier feedback control algorithm called SONIC (self-optimizing narrowband interference canceller), based on minimization of the L2-norm performance measure, can be re-derived using the L1 approach. The resulting robust SONIC algorithm is more robust to heavy-tailed measurement noise, such as the αlpha-stable noise, than the...
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Robust unsupervised georeferencing algorithm for aerial and satellite imagery
PublikacjaIn order to eliminate a human factor and fully automate the process of embedding the spatial localization information in a remote sensed image the integrated georeferencing method was proposed. The paper presents this unsupervised and robust approach which is comprised of pattern recognition, using SIFT-based detector, and RANSAC based outlier removal with matching algorithm.
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Robust pole placement in delta domain for SISO plans
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Robust and Efficient Machine Learning Algorithms for Visual Recognition
PublikacjaIn visual recognition, the task is to identify and localize all objects of interest in the input image. With the ubiquitous presence of visual data in modern days, the role of object recognition algorithms is becoming more significant than ever and ranges from autonomous driving to computer-aided diagnosis in medicine. Current models for visual recognition are dominated by models based on Convolutional Neural Networks (CNNs), which...