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Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

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arXiv 2022年

作者： Zhai, Junyi Dai, Xinliang Jiang, Yuning Xue, Ying Hagenmeyer, Veit Jones, Colin N. Zhang, Xiao-Ping Qingdao China City & Energy Research Institute Suzhou China Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Automatic Control Laboratory EPFL Switzerland School of Electric Power Engineering South China University of Technology Guangzhou China Department of Electronic Electrical and Systems Engineering University of Birmingham Birmingham United Kingdom

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses significant challenges in dealing with the resulting optimal power flow (OPF) problem. In this paper, a recently proposed nonconvex distributed optimization algorithm—Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN), is tailored to solve the nonconvex AC/DC OPF problem for emerging voltage source converter (VSC) based multiterminal high voltage direct current (VSC-MTDC) meshed AC/DC hybrid systems. The proposed scheme decomposes this AC/DC hybrid OPF problem and handles it in a fully distributed way. Compared to the existing state-of-art Alternating Direction Method of Multipliers (ADMM), which is in general, not applicable for nonconvex problems, ALADIN has a theoretical convergence guarantee. Applying these two approaches to VSC-MTDC coupled with an IEEE benchmark AC power system illustrates that the tailored ALADIN outperforms ADMM in convergence speed and numerical robustness. Copyright © 2022, The Authors. All rights reserved.

关键词： Constrained optimization

Future Enterprise as an Intelligent Cyber-Physical System

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IFAC-PapersOnLine 2020年第2期53卷 10873-10878页

作者： Ioan Dumitrache Simona Iuliana Caramihai Ioan Stefan Sacala Mihnea Alexandru Moisescu Dragos Constantin Popescu Department of Automatic Control and Systems Engineering University “Politehnica” of Bucharest Romania Department of Automatics and Industrial Informatics University “Politehnica” of Bucharest Romania

The appearance of new paradigms such as Cyber-Physical systems paradigm has led to the appearance of the next industrial revolution. A Cyber- Physical System based Enterprise involves the usage of physical objects, knowledge structured based on workflows, control systems, human integration, systemic data representation and communication processes. The authors propose the concept of Intelligent Cyber Enterprise (ICE) in order to provide a generic architecture enabling the design of complex enterprise systems enhanced with social and technical capabilities. Components of the architecture have to be independent, facilitating the selection of context-oriented behaviors. In order to facilitate the design of ICE components, the authors have proposed a platform for modeling and evaluation.

关键词： Cyber-Physical systems Intelligent Cyber Enterprise

Resilient Branching MPC for Multi-Vehicle Traffic Scenarios Using Adversarial Disturbance Sequences

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arXiv 2021年

作者： Fors, Victor Olofsson, Björn Frisk, Erik The Division of Vehicular Systems Department of Electrical Engineering Linköping University LinköpingSE-581 83 Sweden The Department of Automatic Control Lund University LundSE-221 00 Sweden

An approach to resilient planning and control of autonomous vehicles in multi-vehicle traffic scenarios is proposed. The proposed method is based on model predictive control (MPC), where alternative predictions of the surrounding traffic are determined automatically such that they are intentionally adversarial to the ego vehicle. This provides robustness against the inherent uncertainty in traffic predictions. To reduce conservatism, an assumption that other agents are of no ill intent is formalized. Simulation results from highway driving scenarios show that the proposed method in real-time negotiates traffic situations out of scope for a nominal MPC approach and performs favorably to state-of-the-art reinforcement-learning approaches without requiring prior training. The results also show that the proposed method performs effectively, with the ability to prune disturbance sequences with a lower risk for the ego vehicle. Copyright © 2021, The Authors. All rights reserved.

关键词： Model predictive control

An exponential stability test for a messenger rna–micro rna ode model

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第4期82卷 11-16页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

In this paper we obtain a numerically tractable test (sufficient condition) for the exponential stability of the unique positive equilibrium point of an ODE system. The result (Theorem 3.1) is based on Lyapunov theory and Linear Ma-trix Inequalities techniques. The ODE model is related to the messengerRNA-microRNA interaction. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： RNA

Actuation attacks on constrained linear systems: a set-theoretic analysis

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IFAC-PapersOnLine 2020年第2期53卷 6963-6968页

作者： P.A. Trodden J.M. Maestre H. Ishii Department of Automatic Control & Systems Engineering University of Sheffield Sheffield UK Department of Systems and Automation Engineering University of Seville Seville Spain Department of Computer Science Tokyo Institute of TechnologyYokohama Japan

This paper considers a constrained discrete-time linear system subject to actuation attacks. The attacks are modelled as false data injections to the system, such that the total input (control input plus injection) satisfies hard input constraints. We establish a sufficient condition under which it is not possible to maintain the states of the system within a compact state constraint set for all possible realizations of the actuation attack. The developed condition is a simple function of the spectral radius of the system, the relative sizes of the input and state constraint sets, and the proportion of the input constraint set allowed to the attacker.

关键词： control problems under conflict or uncertainties Constrained control Robustness

Physics-informed linear regression is competitive with two Machine Learning methods in residential building MPC

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arXiv 2021年

作者： Bünning, Felix Huber, Benjamin Schalbetter, Adrian Aboudonia, Ahmed de Badyn, Mathias Hudoba Heer, Philipp Smith, Roy S. Lygeros, John Empa Urban Energy Systems Laboratory Überlandstrasse 129 Dübendorf8600 Switzerland Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zürich Switzerland

Because physics-based building models are difficult to obtain as each building is individual, there is an increasing interest in generating models suitable for building MPC directly from measurement data. Machine learning methods have been widely applied to this problem and validated mostly in simulation;there are, however, few studies on a direct comparison of different models or validation in real buildings to be found in the literature. Methods that are indeed validated in application often lead to computationally complex non-convex optimization problems. Here we compare physics-informed Autoregressive-Moving-Average with Exogenous Inputs (ARMAX) models to Machine Learning models based on Random Forests and Input Convex Neural Networks and the resulting convex MPC schemes in experiments on a practical building application with the goal of minimizing energy consumption while maintaining occupant comfort, and in a numerical case study. The building has a water-based emission system and is located in temperate climate. We demonstrate that Predictive control leads to savings between 26% and 49% of heating and cooling energy, compared to the building's baseline hysteresis controller. Moreover, we show that all model types lead to satisfactory control performance in terms of constraint satisfaction and energy reduction. However, we also see that the physics-informed ARMAX models have a lower computational burden, and a superior sample efficiency compared to the Machine Learning based models. Moreover, even if abundant training data is available, the ARMAX models have a significantly lower prediction error than the Machine Learning models, which indicates that the encoded physics-based prior of the former cannot independently be found by the latter. Copyright © 2021, The Authors. All rights reserved.

关键词： Model predictive control

Development of a new machine learning-based informatics system for product health monitoring 53

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Development of a new machine learning-based informatics syst...

53rd CIRP Conference on Manufacturing systems, CMS 2020

作者： Papananias, Moschos Obajemu, Olusayo McLeay, Thomas E. Mahfouf, Mahdi Kadirkamanathan, Visakan Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom Sandvik Coromant Mossvägen 10 Sandviken811 34 Sweden

Manufacturing informatics aims to optimize productivity by extracting information from numerous data sources and making decisions based on that information about the process and the parts being produced. Manufacturing processes usually include a series of costly operations such as heat treatment, machining, and inspection to produce high-quality parts. However, performing costly operations when the product conformance to specifications cannot be achievable is not desirable. This paper develops a new machine learning-based informatics system capable of predicting the end product quality so that non-value-adding operations such as inspection can be minimized and the process can be stopped before completion when the part being manufactured fails to meet the design specifications. © 2020 The Authors.

关键词： Multiple linear regression

Delivering Improved Care through Remote Health Monitoring systems by Using Microservices. Case Study: Fall Detection Encompassed into Connected Care

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Delivering Improved Care through Remote Health Monitoring Sy...

International Conference on control systems and Computer Science (CSCS)

作者： Marilena Ianculescu Adriana Alexandru Ionuţ-Emanuel Giura Ana-Mihaela Vasilevschi Communication Digital Applications and Systems Department National Institute for Research and Development in Informatics Bucharest Romania Doctoral School of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Counselors Department National Institute for Research and Development in Informatics Târgovişte Romania Faculty of Electrical Engineering Electronics and Information Technology Târgovişte Romania Valahia University of Târgovişte Târgovişte Romania

Based on today’s modern technologies, patient care can be provided remotely, in a connected way, being, at the same time, personalized, patient-centered and proactive. Such an approach can be achieved using Remote Health Monitoring systems (RHMS). In case of elderly people, dramatic permanent deteriorations of their health status can be caused by falls. The seniors’ health and life style monitoring and the detection and/or prevention of falls can be done by such RHMS, an example being the RO-SmartAgeing system developed inside “Non-invasive Monitoring System and Health Assessment of the Elderly in a Smart Environment (RO-SmartAgeing)” research project. The paper presents the problem of using microservices for optimizing the architecture and functionalities of RO-SmartAgeing system, and the way in which the problems of ensuring the security of patient data can be solved.

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Replay Attack Detection Based on Parity Space Method for Cyber-Physical systems

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arXiv 2023年

作者： Zhao, Dong Shi, Yang Ding, Steven X. Li, Yueyang Fu, Fangzhou School of Cyber Science and Technology Beihang University Beijing100191 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg47057 Germany School of Electrical Engineering University of Jinan Jinan250022 China School of Aeronautics and Astronautics Sun Yat-sen University Shenzhen518107 China

The replay attack detection problem is studied from a new perspective based on parity space method in this paper. The proposed detection methods have the ability to distinguish system fault and replay attack, handle both input and output data replay, maintain certain control performance, and can be implemented conveniently and efficiently. First, the replay attack effect on the residual is derived and analyzed. The residual change induced by replay attack is characterized explicitly and the detection performance analysis based on two different test statistics are given. Second, based on the replay attack effect characterization, targeted passive and active design for detection performance enhancement are proposed. Regarding the passive design, four optimization schemes regarding different cost functions are proposed with optimal parity matrix solutions, and the unified solution to the passive optimization schemes is obtained;the active design is enabled by a marginally stable filter so as to enlarge the replay attack effect on the residual for detection. Simulations and comparison studies are given to show the effectiveness of the proposed methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Cyber Physical System