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2nd International Symposium on Combinatorial Optimization, ISCO 2012

作者： Ausiello, Giorgio Italiano, Giuseppe F. Laura, Luigi Nanni, Umberto Sarracco, Fabiano Dep. of Computer Control and Management Engineering Antonio Ruberti Sapienza Univ. of Rome Via Ariosto 25 Roma 00185 Italy Dep. of Computer Science Systems and Production Univ. of Rome Tor Vergata Via del Politecnico 1 Roma 00133 Italy

ISBN: (纸本)9783642321467

The cost of hyperpaths in directed hypergraphs can be measuread in various different ways, which have been used in a wide set of applications. Not surprisingly, dep.nding on the considered measure function the cost to find optimum hyperpaths may range from NP-hard to linear time. A first solution for finding optimum hyperpaths in case of a superior functions (SUP) can be found in a seminal work by Knuth [5], which generalizes Dijkstra's Algorithm [3] to deal with a grammar problem. In this paper we define a hierarchy of classes of optimization problems based on the properties of the cost measures. After showing that measures can be classified on the basis of the structure of the optimum hyperpath they determine, we present an alternative taxonomy of measure functions, based on their analytic properties, and prove structure theorems that relate the two hierarchies. © 2012 Springer-Verlag.

关键词： Costs

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control system simulation for endoscopie surgical manipulator based on virtual chain approach

Control system simulation for endoscopie surgical manipulato...

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2012 1st International Conference on Innovative engineering Systems, ICIES 2012

作者： Ibrahim, Khalil Ramadan, Ahmed Farmi, Mohamed Kobayashi, Yo Abo-Ismail, Ahmed Fujie, Masakatus G. Mechatronics and Robotics Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Computers and Automatic Control Engineering Dep. Tanta University Tanta Egypt Mechanical Department Mansoura University Mansoura Egypt Faculty of Science and Engineering Waseda University Tokyo Japan

ISBN: (纸本)9781467344388

This paper deals with the design process and the dynamic control simulation of a new type of 4-DOFs parallel mechanism that can be used as an endoscopie surgical manipulator. The proposed mechanism, 2-PUU 2PUS, is designed based on the screw theory and the parallel virtual chain type synthesis method. Based on the structure analysis of the 4-DOF parallel mechanism, the inverse position equation is studied using the inverse analysis theory of kinematics. The design and the stress analysis of the mechanism are investigated using SolidWorks software. The virtual prototype of the parallel mechanism is constructed, and the dynamic simulation is performed using ADAMS™ software. The system model utilizing PID and PI controllers has been built using MATLAB software. A more realistic simulation in accordance with a given bending angle and point to point control is implemented by the use of both ADAMS/MATLAB software. The simulation results showed that this control method has solved the coordinate control for the 4-DOF parallel manipulator so that each output is feedback to the four driving rods. From the results, the tracking performance is achieved. Other control techniques, such as intelligent ones, are recommended to improve the tracking performance and reduce the numerical truncation error. © 2012 IEEE.

关键词： MATLAB

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Smart Healthy Schools: An IoT-enabled concept for multi-room dynamic air quality control

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Internet of Things and Cyber-Physical Systems 2024年第1期4卷 24-31页

作者： Zivelonghi, Alessandro Giuseppi, Alessandro Dep. of Applied Mathematical Science IIS "Calabrese-Levi" VR San Pietro in Cariano Italy PowerConsulting Studio San Pietro in Cariano Verona Italy Dept. of Computer Control and Management Engineering University of Rome "La Sapienza" Via Ariosto 25 Rome00185 Italy

Smart Healthy Schools (SHS) are a new paradigm in building engineering and infection risk control in school buildings where the disciplines of Indoor Air Quality (IAQ), IoT (Internet of Things) and Artificial Intelligence (AI) merge together. In the post-pandemic era, equipping schools with a network of smart IoT sensors has become critical to aspire for the optimal control of the IAQ and lowering the airborne infection risk of several pathogens, indirectly related to cumulated human emitted CO2 levels over time. Thermal energy waste in winter due to improved air renewal remains of major concern but can be well monitored within a SHS monitoring architecture thanks to the flexibility of the LoRaWAN protocol able to process also a large amount of energy and climatic data at room and building scale. In this work, we report the design of the AulaSicura platform, an IoT control system co-designed by the main author and Gizero Energie to implement the SHS paradigm via clearly visible (and audible) alarm signalling in existing and new school buildings. The cloud-based LoRa system is capable of continuous and simultaneous monitoring of a variety of sensors and IAQ parameters including indoor/oudoor temperatures, rel. humidities and human-emitted excess CO2. The multi-room monitoring concept of indoor-CO2 levels allows centralized control of natural ventilation levels in individual classrooms and can handle (quasi)-real-time data, relevant for data post-processing and future developments in (quasi)-real-rime assessment of IAQ and infection risk levels at single room scale. The sensor network is also extensible to up to one thousand of classrooms per LoRa-node allowing centralized control of entire school districts at an urban scale. Moreover, through Modbus-LoRa I/O converters, AulaSicura can also control the same amount of mechanical ventilation units per node either in pure or hybrid mechanical ventilation modes. © 2023 The Authors

关键词： Internet of things

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A novel piezoelectric micro-gripper's control study

A novel piezoelectric micro-gripper's control study

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2011 International Conference on Internet Computing and Information Services, ICICIS 2011

作者： Zeng, Xiangjin Huang, Xinhan Hubei Province Key Laboratory of Intelligent Robot Wuhan Institute of Technology 430073 Wuhan China School of Computer Science and Engineering Wuhan Institute of Technology 430073 Wuhan China Dep. of Control Science and Engineering Huazhong University of Science and Technology 430074 Wuhan China

ISBN: (纸本)9780769545394

In this paper, we develop a micro-gripper that actuated by piezoelectric cantilever for the need of micro parts assembly. The displacement-voltage relationship model is given. For hysteresis of piezoelectric ceramic, we present a mix control algorithm, which employs the hysteresis offset control model based on Dahl and PID control model. The results of micro-assembly prove that the model is efficiency. © 2011 IEEE.

关键词： Hysteresis

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Two-Stage Single-Phase EV On-Board Charger Based on Interleaved Bridgeless AC-DC Converter 5

Two-Stage Single-Phase EV On-Board Charger Based on Interlea...

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5th International Youth Conference on Radio Electronics, Electrical and Power engineering, REEPE 2023

作者： Abdelmomen, Mahmoud Sameh Abdelsalam, Ibrahim Hamad, Mostafa S. Industries Innovate The Technical Company for Engineering Obour Egypt Arab Academy for Science Technology and Maritime Transport College of Engineering and Technology Electrical and Control Engineering Dep. Cairo Egypt Arab Academy for Science Technology and Maritime Transport Research and Development Center Al Alamein Egypt

ISBN: (纸本)9798350399523

This paper presents a two-stage single-phase 3.5kVA on-board charger (OBC) for an electric vehicle (EV) charger that is suitable to be connected to a low-voltage household network. The proposed OBC consists of a front-end converter and a back-end converter. The two-phase bridgeless interleaved converter is used as a front-end converter since it will reduce the current stress on the power electronic switches and improve the overall charger efficacy. For the back-end converter, the LLC resonant network single-active bridge is used to provide galvanic isolation, and it operates a switching frequency high than the resonance frequency to achieve zero-voltage switching. Also, the presented control strategy loops make the proposed OBC have three operating modes (current control mode, fixed input power mode, and voltage control mode) with a smooth transition between the modes during the EV charging process. Finally, the proposed OBC simulation and experimentation are carried out to verify the safe charging operation. Finally, the performance of the proposed OBC and the proposed control strategy was verified using PSCAD/EMTDC simulation, such as first the performance of the current control mode was first tested, and the full charging cycle was simulated. © 2023 IEEE.

关键词： Charging (batteries)

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Output feedback tracking of nonholonomic systems in chained form

Output feedback tracking of nonholonomic systems in chained ...

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1999 European control Conference, ECC 1999

作者： Lefeber, E. Robertsson, A. Nijmeijer, H. Faculty of Mathematical Science Dep. of Systems Signals and Control. University of Twente P.O. Box 217 Enschede7500 AE Netherlands Dep. of Automatic Control Lund Institute of Technology Lund University P.O. Box 118 LundSE-221 00 Sweden Faculty of Mathematical Science Dep. of Systems Signals and Control Univer. of Twente P.O. Box 217 Enschede7500 AE Netherlands Faculty of Mechanical Engineering Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands

ISBN: (纸本)9783952417355

In this paper we study the tracking problem for the class of non-holonomic systems in chained form. In particular, with as outputs the first and last state component of the chained form, we suggest a solution for the output tracking problem by combining a time-varying state feedback controller with an observer for the chained form system. For the stability analysis of the 'certainty equivalence type' of controller we use a cascaded systems approach. The resulting closed loop system is globally K-exponentially stable. © 1999 EUCA.

关键词： Closed loop systems

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An analysis of lockergoga ransomware

An analysis of lockergoga ransomware

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2019 IEEE East-West Design and Test Symposium, EWDTS 2019

作者： Adamov, Alexander Carlsson, Anders Surmacz, Tomasz NioGuard Security Lab Kharkiv National University of Radio Electronics Kharkiv Ukraine Dep. of Computer Science Blekinge Institute of Technology Karlskrona Sweden Institute of Computer Engineering Control and Robotics Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (纸本)9781728110035

This paper contains an analysis of the LockerGoga ransomware that was used in the range of targeted cyberattacks in the first half of 2019 against Norsk Hydra-A world top 5 aluminum manufacturer, as well as the US chemical enterprises Hexion, and Momentive-Those companies are only the tip of the iceberg that reported the attack to the public. The ransomware was executed by attackers from inside a corporate network to encrypt the data on enterprise servers and, thus, taking down the information control systems. The intruders asked for a ransom to release a master key and decryption tool that can be used to decrypt the affected files. The purpose of the analysis is to find out tactics and techniques used by the LockerGoga ransomware during the cryptolocker attack as well as an encryption model to answer the question if the encrypted files can be decrypted with or without paying a ransom. The scientific novelty of the paper lies in an analysis methodology that is based on various reverse engineering techniques such as multi-process debugging and using open source code of a cryptographic library to find out a ransomware encryption model. © 2019 IEEE.

关键词： Reverse engineering

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Solving the vehicle routing problem with deep reinforcement learning

arXiv

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arXiv 2022年

作者： Foà, Simone Coppola, Corrado Grani, Giorgio Palagi, Laura Sapienza University of Rome Dep. of Computer Science Control and Management Engineering Rome Italy Sapienza University of Rome Dep. of Statistical Science Rome Italy

Recently, the applications of the methodologies of Reinforcement Learning (RL) to NP-Hard Combinatorial optimization problems has become a popular topic. This is essentially due to the nature of the traditional combinatorial algorithms, often based on a trial-and-error process. RL aims at automating this process. At this regard, this paper focuses on the application of RL for the Vehicle Routing Problem (VRP), a famous combinatorial problem that belongs to the class of NP-Hard problems. In this work, as first, the problem is modeled as a Markov Decision Process (MDP) and then the PPO method (which belongs to the Actor-Critic class of Reinforcement learning methods) is applied. In a second phase, the neural architecture behind the Actor and Critic has been established, choosing to adopt a neural architecture based on the Convolutional neural networks, both for the Actor and the Critic. This choice resulted effective to address problems of different sizes. Experiments performed on a wide range of instances show that the algorithm has good generalization capabilities and can reach good solutions in a short time. Comparisons between the algorithm proposed and the state-of-the-art solver OR − TOOLS show that the latter still outperforms the Reinforcement learning algorithm. However, there are future research perspectives, that aim to upgrade the current performance of the algorithm *** Codes 90-08 © 2022, CC BY.

关键词： Reinforcement learning

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On-Board Battery Charger Based-on Multifunctional Two-Stage Topology for Electric Vehicles

On-Board Battery Charger Based-on Multifunctional Two-Stage ...

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2023 IEEE PES/IAS PowerAfrica, PowerAfrica 2023

作者： Alajmi, Bader N. Abdelsalam, Ibrahim Marei, Mostafa I. Ahmed, Nabil A. College of Technological Studies Electrical Engineering Technology Department Shuwaikh Kuwait College of Engineering & Technology Arab Academy for Science Technology & MaritimeTransport Electrical and Control Engineering Dep. Cairo Egypt Ain Shams University Faculty of Engineering Electrical Power and Machines Department Cairo Egypt

ISBN: (纸本)9798350337556

This paper proposed a multifunctional two-stage topology based on-board charger (OBC) for electric vehicles (EV s). The proposed two-stage topology is composed of three indep.ndent front-end ac-dc converters that are utilized to provide the dc input for three indep.ndent back-end dc-dc converters. The output side of the back-end converters are connected in parallel to reduce the components rating and increase reliability of the OBC. Single active bridge (SAB) with LLC resonant tank is utilized for each back-end converter to reduce the switching losses and improve the charger efficiency. Moreover, the proposed front end-converter can be connected to either three-phase supply, and behave as level '2' charger, or single-phase supply to operate as level '1' charger. Only two transfer switches are used to connect the input terminals of the three front-end converters in parallel to the single-phase supply. This action enables interleaved operation of the proposed converter. Furthermore, the proposed control algorithm for the front-end converter regulates the charging voltage and current, keeps sinusoidal supply current with a high power factor, and maintains balanced three-phase supply currents. The proposed OBC is simulated using PSCAD/EMTDC to verify the dynamic performance and to demonstrate the multifunctional operation of the control algorithm. © 2023 IEEE.

关键词： Topology

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An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents

arXiv

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arXiv 2021年

作者： Monaci, Marta Agasucci, Valerio Grani, Giorgio Sapienza University of Rome Dep. of Computer Science Control and Management Engineering Rome Italy Sapienza University of Rome Dep. of Statistics Rome Italy

In this work, we present a method that applies Deep Reinforcement Learning, an approximate dynamic programming procedure using deep neural networks, to the job shop scheduling problem (JSSP). The aim is to show that a greedy-like heuristic trained on a subset of problems, can effectively generalize to some extent to unseen instances, and be competitive compared to other methods. We model the JSSP as a Markov Decision Process and we exploit the efficacy of reinforcement learning to solve the problem. We adopt an actor-critic scheme based on policy gradients, specifically the Proximal Policy Gradient method, where the action taken by the agent is influenced by policy considerations on the state-value function. The procedures take into account the challenging nature of JSSP, where the state and the action space change for every instance and after each decision. To tackle this variability, we introduced a novel model based on two incident Long-Short Term Memory networks, followed by an encoding model, different in structure for both the actor and the critic. Experiments show the algorithm reaches good solutions in a short time, proving that is possible to generate new greedy heuristics just from learning-based methodologies. We compared our algorithms against several established heuristics, an adaptive method, a commercial solver based on branch and cut, and another approach based on Deep Reinforcement Learning, proving the validity of the proposed method in terms of time and makespan. The model can generalize, to some extent, to larger problems originating from a different *** Codes 90-08 © 2021, CC BY.

关键词： Reinforcement learning

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