Integral backstepping control for trajectory tracking of a hybrid vehicle

International audienceThis article is focused on the trajectory tracking using a hybrid terrestrial aerial vehicle. An integral back-stepping control is proposed for the UAV vehicle mode. In addition, a nested saturation control is developed and applied to regulate the position of the cart vehicle. These control laws are validated by simulations and some experimental results on position control was performed by applying the techniques aforementioned. I. SYSTEM DESCRIPTION In this work control laws are developed for trajectory tracking of a hybrid terrestrial aerial vehicle. These kinds of vehicles have the advantage to be used as a flying vehicle or as a cart depending on the situation. Some situations may be when the vehicle find an obstacle and it has to take the more convenient mode of operation to overcome or to avoid the obstacle. Controlling these hybrid vehicles becomes a challenge. It is necessary to design and implement control laws for the trajectory following in the air and over the floor. The control strategy has to generate a smooth transition when the drone is passing from air to floor or vice versa. There are several works dedicated to path following with hexarotors and also for carts, see for example [1]–[3]. This work considers a particular hybrid vehicle : a mini-UAV that is converted in a cart by attaching to it two wheels without any additional motors as in Fig. 1. The orientation and position of the cart will be controlled by the yaw and pitch angles and by the thrust generated by its helices. Among its characteristics, the thrust direction can be inversed as a result of the pitch angle variation. Therefore, the cart-drone can move forward or backward depending on the sign of pitch angle. This hybrid vehicle in terrestrial mode can turn around z axis. It is also a nonholonomic system because it is not capable to move on the wheels axis direction in terrestrial mode. For more references in cart control refer to [4]–[6]

Velocity control of mini-UAV using a helmet system

International audienceThe usage of a helmet to command a mini-unmanned aerial vehicle (mini-UAV), is a telepresence system that connects the operator to the vehicle. This paper proposes a system which remotely allows the connection of a pilot's head motion and the 3D movements of a mini-UAVs. Two velocity control algorithms have been tested in order to manipulate the system. Results demonstrate that these movements can be used as reference inputs of the controller of the mini-UAV

CrimeNet: Neural Structured Learning using Vision Transformer for violence detection

The state of the art in violence detection in videos has improved in recent years thanks to deep learning models, but it is still below 90% of average precision in the most complex datasets, which may pose a problem of frequent false alarms in video surveillance environments and may cause security guards to disable the artificial intelligence system. In this study, we propose a new neural network based on Vision Transformer (ViT) and Neural Structured Learning (NSL) with adversarial training. This network, called CrimeNet, outperforms previous works by a large margin and reduces practically to zero the false positives. Our tests on the four most challenging violence-related datasets (binary and multi-class) show the effectiveness of CrimeNet, improving the state of the art from 9.4 to 22.17 percentage points in ROC AUC depending on the dataset. In addition, we present a generalisation study on our model by training and testing it on different datasets. The obtained results show that CrimeNet improves over competing methods with a gain of between 12.39 and 25.22 percentage points, showing remarkable robustness.MCIN/AEI/ 10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR ” HORUS project - Grant n. PID2021-126359OB-I0

Position Control of a Quadrotor under External Constant Disturbance

International audienceIn the present work, an adaptive backstepping algorithm is developed in order to counteract the effects of disturbances. These disturbances are modeled as a constant force in the translational model part and as a constant torque in the orientation model part. We make the deduction of the mathematical expression for the proposed control algorithm and also we show its performance in simulation. Additionally, we include some experiments for validating the results obtained via simulation

On the Picard-Fuchs Equations for Massive N=2 Seiberg-Witten Theories

A new method to obtain the Picard-Fuchs equations of effective, N=2 supersymmetric gauge theories with massive matter hypermultiplets in the fundamental representation is presented. It generalises a previously described method to derive the Picard-Fuchs equations of both pure super Yang-Mills and supersymmetric gauge theories with massless matter hypermultiplets. The techniques developed are well suited to symbolic computer calculations.Comment: 29 pages, uses phyzzx.te

Acceso venoso central mediante cápsulas de inyección subcutáneas. Serie de 124 dispositivos

Presentamos una serie de 111 pacientes (límites: 9 meses - 78 años) en los que se colocaron 124 dispositivos como modalidad de acceso venoso central. Se analizan las complicaciones aparecidas durante su utilización, que actualmente sobrepasa los 1.100 meses, y se comentan aspectos técnicos de colocación con influencia sobre la morbilidad del sistema. La media actual de funcionamiento se sitúa en 9,9 meses por persona, con una tasa de complicaciones del 19 %

Interpretable clinical time-series modeling with intelligent feature selection for early prediction of antimicrobial multidrug resistance

Electronic health records provide rich, heterogeneous data about the evolution of the patients’ health status. However, such data need to be processed carefully, with the aim of extracting meaningful information for clinical decision support. In this paper, we leverage interpretable (deep) learning and signal processing tools to deal with multivariate time-series data collected from the Intensive Care Unit (ICU) of the University Hospital of Fuenlabrada (Madrid, Spain). The presence of antimicrobial multidrug-resistant (AMR) bacteria is one of the greatest threats to the health system in general and to the ICUs in particular due to the critical health status of the patients therein. Thus, early identification of bacteria at the ICU and early prediction of their antibiotic resistance are key for the patients’ prognosis. While intelligent data-based processing and learning schemes can contribute to this early prediction, their acceptance and deployment in the ICUs require the automatic schemes to be not only accurate but also understandable by clinicians. Accordingly, we have designed trustworthy intelligent models for the early prediction of AMR based on the combination of meaningful feature selection with interpretable recurrent neural networks. These models were created using irregularly sampled clinical measurements, both considering the health status of the patient and the global ICU environment. We explored several strategies to cope with strongly imbalance data, since only a few ICU patients are infected by AMR bacteria. It is worth noting that our approach exhibits a good balance between performance and interpretability, especially when considering the difficulty of the classification task at hand. A multitude of factors are involved in the emergence of AMR (several of them not fully understood), and the records only contain a subset of them. In addition, the limited number of patients, the imbalance between classes, and the irregularity of the data render the problem harder to solve. Our models are also enriched with SHAP post-hoc interpretability and validated by clinicians who considered model understandability and trustworthiness of paramount concern for pragmatic purposes. Moreover, we use linguistic fuzzy systems to provide clinicians with explanations in natural language. Such explanations are automatically generated from a pool of interpretable rules that describe the interaction among the most relevant features identified by SHAP. Notice that clinicians were especially satisfied with new insights provided by our models. Such insights helped them to trust the automatic schemes and use them to make (better) decisions to mitigate AMR spreading in the ICU. All in all, this work paves the way towards more comprehensible time-series analysis in the context of early AMR prediction in ICUs and reduces the time of detection of infectious diseases, opening the door to better hospital care.This work is supported by the Spanish NSF grants PID2019-106623RB-C41 (BigTheory), PID2019-105032GB-I00 (SPGraph), PID2019-107768RA-I00 (AAVis-BMR), RTI2018-099646-B-I00 (ADHERE-U); the Galician Ministry of Education, University and Professional Training grants ED431F 2018/02 (eXplica-IA) and ED431G2019/04; the Instituto de Salud Carlos III, Spain grant DTS17/00158; as well as the Community of Madrid in the framework of the Multiannual Agreement with Rey Juan Carlos University in line of action 1, “Encouragement of Young Phd students investigation” Project Ref. F661 (Mapping-UCI). Sergio M. Aguero is a recipient of the Predoctoral Contracts for Trainees URJC Grant (PREDOC21-036). Jose M. Alonso-Moral is a Ramon Cajal Researcher (RYC-2016-19802).S

Structural evolution of the El Salvador Fault Zone: an evolving fault system within a volcanic arc.

The El Salvador Fault Zone, firstly identifiedafter the 13th February 2001 Mw 6.6 El Salvador earthquake, is a 150 km long,20 km wide right-lateral strike-slip fault system. Ruptures along the ESFZ arethought to be responsible for most of the historical destructive earthquakesalong the El Salvador Volcanic Arc, as well as for most of the currentseismicity of the area. In this work, we focus on the geological setting of thefault zone by describing its geomorphology and structure, using field-based observations,digital terrain modelling, and aerial photograph interpretation with the aim atcontributing to the understanding of the ESFZ slip behaviour. In particular, weaddress the ESFZ structure, kinematics and evolution with time. The ESFZ is a complex set of traces divided inmajor rupture segments characterized by different geometry, kinematics andgeomorphic expressions. Natural fault exposures and paleoseismic trenchesexcavated along the fault show that the strike slip deformation is distributedin several planes. Both geometry and kinematics of the fault zone areconsistent with a transtensional strain regime.The estimated geological slip-rate for the mainfault segments by paleoseismic trenches and displaced geomorphic features impliesa deficit in velocity of the fault compared to the available GPS velocitiesdata. The high vertical scarps of some fault segments would require quaternaryslip rates not coherent neither with measured GPS velocities nor with sliprates obtained from paleoseismic analysis. This mismatch suggests apre-existing graben structure that would be inherited from the previousregional roll back related extensional stage. We consider that the ESFZ isusing this relict structure to grow up along it. As a result, we propose amodel for ESFZ development consistent with all these observations.La Zona de Falla de El Salvador (ZFES) es un sistema de falla de desgarre dextral de 150 km de longitud y 20 de anchura, que fue identificada por primera vez después del terremoto de Mw 6.6 de El Salvador de febrero de 2001. La mayoría de la sismicidad y de los terremotos históricos destructivos producidos en el arco volcánico salvadoreño han sido producidos por la ruptura de la ZFES. Este trabajo se centra en el marco geológico de la zona de falla describiendo su geomorfología y su estructura a través de observaciones de campo, del estudio de los modelos digitales del terreno y de la interpretación de las fotografías aéreas, con el objetivo de avanzar en el conocimiento del comportamiento de la ZFES. En concreto trataremos del estudio de la estructura, la cinemática y la evolución de la ZFES. La ZFES es un complejo sistema de fallas divididas en varios segmentos que se diferencian en la geometría, la cinemática y la expresión geomorfológica. En los afloramientos de la falla, así como en las trincheras paleosismicas excavadas se ha observado que la deformación de desgarre está distribuida en varios planos y tanto la geometría como la cinemática de la zona de falla indican que la ZFES está bajo un régimen de deformación transtensional. La tasa de deformación estimada para los principales segmentos a través del estudio paleosísmico y del análisis de indicadores geomorfológicos desplazados nos muestra un déficit de velocidad para la falla si lo comparamos con los datos obtenidos por GPS. Estos datos tampoco ayudan a explicar la existencia de grandes escarpes verticales que se observan en algunos segmentos de la falla, y que requerirían tasas de deformación muy elevadas. Esta discrepancia sugiere la existencia de una estructura de graben preexistente que puedo ser producida por el “roll-back” de la placa y que creó una fase extensional en el arco volcánico. En este trabajo consideramos que la ZFES está actualmente desarrollándose sobre la estructura extensional relicta y como resultado proponemos un modelo estructural consistente con estas observaciones