Robust Cooperative Manipulation without Force/Torque Measurements: Control Design and Experiments

This paper presents two novel control methodologies for the cooperative manipulation of an object by N robotic agents. Firstly, we design an adaptive control protocol which employs quaternion feedback for the object orientation to avoid potential representation singularities. Secondly, we propose a control protocol that guarantees predefined transient and steady-state performance for the object trajectory. Both methodologies are decentralized, since the agents calculate their own signals without communicating with each other, as well as robust to external disturbances and model uncertainties. Moreover, we consider that the grasping points are rigid, and avoid the need for force/torque measurements. Load distribution is also included via a grasp matrix pseudo-inverse to account for potential differences in the agents' power capabilities. Finally, simulation and experimental results with two robotic arms verify the theoretical findings

AWARE: Platform for Autonomous self-deploying and operation of Wireless sensor-actuator networks cooperating with unmanned AeRial vehiclEs

This paper presents the AWARE platform that seeks to enable the cooperation of autonomous aerial vehicles with ground wireless sensor-actuator networks comprising both static and mobile nodes carried by vehicles or people. Particularly, the paper presents the middleware, the wireless sensor network, the node deployment by means of an autonomous helicopter, and the surveillance and tracking functionalities of the platform. Furthermore, the paper presents the first general experiments of the AWARE project that took place in March 2007 with the assistance of the Seville fire brigades

Autonomous Demand Side Management of Electric Vehicles

There is an error in the table of content, where publication A and B have swiched places.Demand-side management approaches that exploit the temporal flexibility of electric vehicles have attracted much attention in recent years due to the increasing market penetration. These demand-side management measures contribute to alleviating the burden on the power system, especially in distribution grids where bottlenecks are more prevalent. Electric vehicles can be defined as an attractive asset for distribution system operators, which have the potential to provide grid services if properly managed. In this thesis, first, a systematic investigation is conducted for two typically employed demand-side management methods reported in the literature: A voltage droop control-based approach and a market-driven approach. Then a control scheme of decentralized autonomous demand side management for electric vehicle charging scheduling which relies on a unidirectionally communicated grid-induced signal is proposed. In all the topics considered, the implications on the distribution grid operation are evaluated using a set of time series load flow simulations performed for representative Austrian distribution grids. Droop control mechanisms are discussed for electric vehicle charging control which requires no communication. The method provides an economically viable solution at all penetrations if electric vehicles charge at low nominal power rates. However, with the current market trends in residential charging equipment especially in the European context where most of the charging equipment is designed for 11 kW charging, the technical feasibility of the method, in the long run, is debatable. As electricity demand strongly correlates with energy prices, a linear optimization algorithm is proposed to minimize charging costs, which uses next-day market prices as the grid-induced incentive function under the assumption of perfect user predictions. The constraints on the state of charge guarantee the energy required for driving is delivered without failure. An average energy cost saving of 30% is realized at all penetrations. Nevertheless, the avalanche effect due to simultaneous charging during low price periods introduces new power peaks exceeding those of uncontrolled charging. This obstructs the grid-friendly integration of electric vehicles.publishedVersio

Optimal power tracking for autonomous demand side management of electric vehicles

Increasing electric vehicle penetration leads to undesirable peaks in power if no proper coordination in charging is implemented. We tested the feasibility of electric vehicles acting as flexible demands responding to power signals to minimize the system peaks. The proposed hierarchical autonomous demand side management algorithm is formulated as an optimal power tracking problem. The distribution grid operator determines a power signal for filling the valleys in the non-electric vehicle load profile using the electric vehicle demand flexibility and sends it to all electric vehicle controllers. After receiving the control signal, each electric vehicle controller re-scales it to the expected individual electric vehicle energy demand and determines the optimal charging schedule to track the re-scaled signal. No information concerning the electric vehicles are reported back to the utility, hence the approach can be implemented using unidirectional communication with reduced infrastructural requirements. The achieved results show that the optimal power tracking approach has the potential to eliminate additional peak demands induced by electric vehicle charging and performs comparably to its central implementation. The reduced complexity and computational overhead permits also convenient deployment in practice.publishedVersio

Optimal power tracking for autonomous demand side management of electric vehicles

publishedVersio

Кибербезопасность в образовательных сетях

The paper discusses the possible impact of digital space on a human, as well as human-related directions in cyber-security analysis in the education: levels of cyber-security, social engineering role in cyber-security of education, “cognitive vaccination”. “A Human” is considered in general meaning, mainly as a learner. The analysis is provided on the basis of experience of hybrid war in Ukraine that have demonstrated the change of the target of military operations from military personnel and critical infrastructure to a human in general. Young people are the vulnerable group that can be the main goal of cognitive operations in long-term perspective, and they are the weakest link of the System.У статті обговорюється можливий вплив цифрового простору на людину, а також пов'язані з людиною напрямки кібербезпеки в освіті: рівні кібербезпеки, роль соціального інжинірингу в кібербезпеці освіти, «когнітивна вакцинація». «Людина» розглядається в загальному значенні, головним чином як та, що навчається. Аналіз надається на основі досвіду гібридної війни в Україні, яка продемонструвала зміну цілей військових операцій з військовослужбовців та критичної інфраструктури на людину загалом. Молодь - це вразлива група, яка може бути основною метою таких операцій в довгостроковій перспективі, і вони є найслабшою ланкою системи.В документе обсуждается возможное влияние цифрового пространства на человека, а также связанные с ним направления в анализе кибербезопасности в образовании: уровни кибербезопасности, роль социальной инженерии в кибербезопасности образования, «когнитивная вакцинация». «Человек» рассматривается в общем смысле, в основном как ученик. Анализ представлен на основе опыта гибридной войны в Украине, которая продемонстрировала изменение цели военных действий с военного персонала и критической инфраструктуры на человека в целом. Молодые люди являются уязвимой группой, которая может быть главной целью когнитивных операций в долгосрочной перспективе, и они являются самым слабым звеном Систем