Search results for "Robustne"
showing 10 items of 515 documents
Transport policy and climate change: How to decide when experts disagree
2008
Abstract Transport is the sector with the fastest growth of greenhouse gases emissions in many countries. Accumulation of these emissions may cause uncertain and irreversible adverse climate change impacts. In this context, we use the analytic hierarchy process (AHP) to face the question on how to select the best transport policy if the experts have different opinions and beliefs on the occurrence of these impacts. Thus, both the treatment of uncertainty and dissent are examined for the ranking of transport policies. The opinions of experts have been investigated by a means of a survey questionnaire. A sensitivity analysis of the experts’ weights and the criteria’ weights confirms the robus…
Stability analysis for stochastic hybrid systems: A survey
2014
This survey addresses stability analysis for stochastic hybrid systems (SHS), which are dynamical systems that combine continuous change and instantaneous change and that also include random effects. We re-emphasize the common features found in most of the models that have appeared in the literature, which include stochastic switched systems, Markov jump systems, impulsive stochastic systems, switching diffusions, stochastic impulsive systems driven by renewal processes, diffusions driven by Lévy processes, piecewise-deterministic Markov processes, general stochastic hybrid systems, and stochastic hybrid inclusions. Then we review many of the stability concepts that have been studied, inclu…
Robust Multi-Objective Optimal dispatch of Distributed Energy Resources in Micro-Grids
2011
Modern distribution systems are implemented through micro grids: small power networks where generation is close to consumption and ICT supports the coordinated management of the different energy resources. In such systems, the central control unit manages energy dispatch from the different sources according to different criteria (technical, economical and environmental) and takes care of tertiary regulation. Such optimization for the tertiary regulation is performed with a time interval that typically is of 24 hours. This is due to the fact that it is necessary to take into account the charge and discharge cycles of storage systems. On the other hand, such long time leads to large errors in…
Uncertainty assessment of a membrane bioreactor model using the GLUE methodology
2010
A mathematical model for the simulation of physical-biological organic removal by means of a membrane bioreactor (MBR) has been previously developed and tested. This paper presents an analysis of the uncertainty of the MBR model. Particularly, the research explores the applicability of the Generalised Likelihood Uncertainty Estimation (GLUE) methodology that is one of the most widely used methods for investigating the uncertainties in the hydrology and that now on is spreading in other research field. For the application of the GLUE methodology, several Monte Carlo simulations have been run varying the all model influential parameters simultaneously. The model was applied to an MBR pilot pl…
High Quality Reconstruction of Dynamic Objects using 2D-3D Camera Fusion
2017
International audience; In this paper, we propose a complete pipeline for high quality reconstruction of dynamic objects using 2D-3D camera setup attached to a moving vehicle. Starting from the segmented motion trajectories of individual objects, we compute their precise motion parameters, register multiple sparse point clouds to increase the density, and develop a smooth and textured surface from the dense (but scattered) point cloud. The success of our method relies on the proposed optimization framework for accurate motion estimation between two sparse point clouds. Our formulation for fusing it closest-point and it consensus based motion estimations, respectively in the absence and pres…
Higher-Fidelity Frugal and Accurate Quantile Estimation Using a Novel Incremental <italic>Discretized</italic> Paradigm
2018
Traditional pattern classification works with the moments of the distributions of the features and involves the estimation of the means and variances. As opposed to this, more recently, research has indicated the power of using the quantiles of the distributions because they are more robust and applicable for non-parametric methods. The estimation of the quantiles is even more pertinent when one is mining data streams. However, the complexity of quantile estimation is much higher than the corresponding estimation of the mean and variance, and this increased complexity is more relevant as the size of the data increases. Clearly, in the context of infinite data streams, a computational and sp…
Robust Neural Machine Translation: Modeling Orthographic and Interpunctual Variation
2020
Neural machine translation systems typically are trained on curated corpora and break when faced with non-standard orthography or punctuation. Resilience to spelling mistakes and typos, however, is crucial as machine translation systems are used to translate texts of informal origins, such as chat conversations, social media posts and web pages. We propose a simple generative noise model to generate adversarial examples of ten different types. We use these to augment machine translation systems’ training data and show that, when tested on noisy data, systems trained using adversarial examples perform almost as well as when translating clean data, while baseline systems’ performance drops by…
Robust model-following control of parallel UPS single-phase inverters
2008
This paper presents a robust control technique applied to modular uninterruptible power-supply (UPS) inverters operating in parallel. When compared to conventional proportional-integral (PI) control, the proposed technique improves the response of the output voltage to load steps and to high distorted output currents, reducing the distortion of the output voltage. Furthermore, an excellent distribution of currents between modules is achieved, resulting in fine power equalization between the inverters on stream. The crossover frequency of the different loop gains involved is moderate, so that robustness to variations of the operation point and to modeling uncertainties is achieved. A compara…
Comprehensive Experimental Analysis of Handcrafted Descriptors for Face Recognition
2018
Over the past few decades, LBP descriptor, which shown its high robustness in extracting discriminative features from an image, has been successfully applied in diverse challenging computer vision applications including face recognition. The efficiency and usability of the LBP operator and its success in various real world applications has inspired the development of much new powerful LBP variants. Indeed, after the appearance of the LBP operator, several renowned extensions and modifications of LBP have been proposed in the literature to the point that it can be difficult to recognize their respective LBP-related strategies, strengths and weaknesses according to a given application, and th…
Asynchronous sensor fusion of GPS, IMU and CAN-based odometry for heavy-duty vehicles
2021
[EN] In heavy-duty vehicles, multiple signals are available to estimate the vehicle's kinematics, such as Inertial Measurement Unit (IMU), Global Positioning System (GPS) and linear and angular speed readings from wheel tachometers on the internal Controller Area Network (CAN). These signals have different noise variance, bandwidth and sampling rate (being the latter, possibly, irregular). In this paper we present a non-linear sensor fusion algorithm allowing asynchronous sampling and non-causal smoothing. It is applied to achieve accuracy improvements when incorporating odometry measurements from CAN bus to standard GPS+IMU kinematic estimation, as well as the robustness against missing da…