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| 1 | Resilience Against Replay Attacks:A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems显示文摘In this paper,a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed.The methodological starting point relies on a smart use of predictive arguments with a twofold aim:1)Promptly detect malicious agent behaviors affecting normal system operations;2)Apply specific control actions,based on predictive ideas,for mitigating as much as possible undesirable domino effects resulting from adversary operations.Specifically,the multi-agent system is topologically described by a leader-follower digraph characterized by a unique leader and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to instantaneously recognize the attacked agent.Finally,numerical simulations are carried out to show benefits and effectiveness of the proposed approach. | Giuseppe Franzè Francesco Tedesco Domenico Famularo | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，3： | 5 |
| 2 | Genetic variation in eggplant for Nitrogen Use Efficiency under contrasting NO3^- supply显示文摘Eggplant(Solanum melongena L.) yield is highly sensitive to N fertilization, the excessive use of which is responsible for environmental and human health damage.Lowering N input together with the selection of improved Nitrogen-Use-Efficiency(NUE) genotypes, more able to uptake, utilize, and remobilize N available in soils, can be challenging to maintain high crop yields in a sustainable agriculture. The aim of this study was to explore the natural variation among eggplant accessions from different origins, in response to Low(LN) and High(HN)Nitrate(NO3^-) supply, to identify NUE-contrasting genotypes and their NUE-related traits, in hydroponic and greenhouse pot experiments. Two eggplants, AM222 and AM22, were identified as N-use efficient and inefficient,respectively, in hydroponic, and these results were confirmed in a pot experiment, when crop yield was also evaluated. Overall, our results indicated the key role of Nutilization component(NUt E) to confer high NUE. The remobilization of N from leaves to fruits may be a strategy to enhance NUt E, suggesting glutamate synthase as a key enzyme. Further, omics technologies will be used for focusing on C-N metabolism interacting networks. The availability of RILs from two other selected NUE-contrasting genotypes will allow us to detect major genes/quantitative trait loci related to NUE. | Antonio Mauceri Laura Bassolino Antonio Lupini Franz Badeck Fulvia Rizza Massimo Schiavi Laura Toppino Maria Rosa Abenavoli Giuseppe L.Rotino Francesco Sunseri | 2020 | Journal of Integrative Plant Biology2020，62，4： | 3 |
| 3 | A Resilient Control Strategy for Cyber-Physical Systems Subject to Denial of Service Attacks:A Leader-Follower Set-Theoretic Approach显示文摘Multi-agent systems are usually equipped with open communication infrastructures to improve interactions efficiency,reliability and sustainability.Although technologically costeffective,this makes them vulnerable to cyber-attacks with potentially catastrophic consequences.To this end,we present a novel control architecture capable to deal with the distributed constrained regulation problem in the presence of time-delay attacks on the agents’communication infrastructure.The basic idea consists of orchestrating the interconnected cyber-physical system as a leader-follower configuration so that adequate control actions are computed to isolate the attacked unit before it compromises the system operations.Simulations on a multi-area power system confirm that the proposed control scheme can reconfigure the leader-follower structure in response to denial ofservice(DoS)attacks. | Giuseppe Franzè Domenico Famularo Walter Lucia Francesco Tedesco | 2020 | IEEE/CAA Journal of Automatica Sinica2020，7，5： | 3 |
| 4 | Resilient Control in Large-Scale Networked Cyber-Physical Systems: Guest Editorial显示文摘RECENT advances in sensing,communication and computing have open the door to the deployment of largescale networks of sensors and actuators that allow fine-grain monitoring and control of a multitude of physical processes and infrastructures.The appellation used by field experts for these paradigms is Cyber-Physical Systems(CPS)because the dynamics among computers,networking media/resources and physical systems interact in a way that multi-disciplinary technologies(embedded systems,computers,communications and controls)are required to accomplish prescribed missions.Moreover,they are expected to play a significant role in the design and development of future engineering applications such as smart grids,transportation systems,nuclear plants and smart factories. | Giuseppe Franze Giancarlo Fortino Xianghui Cao Giuseppe Maria Luigi Sarne Zhen Song | 2020 | IEEE/CAA Journal of Automatica Sinica2020，7，5： | 1 |
| 5 | Blood pressure control and improved cardiovascular outcomes in the International Verapamil SR-Trandolapril Study显示文摘 | Franz Messerli George Bakris | 2007 | J Hypertens2007，50，2： | 1 |
| 6 | A nonlinear sum-of-squares model predictive control approach显示文摘 | Giuseppe Franze | 2010 | IEEE Trans on Automatic Control2010，55，6： | 1 |
| 7 | Diverticular disease in the elderly 显示文摘 | Giuseppe Comparato Alberto Pilotto Angelo Franze | 2007 | Dig Dis2007，25，： | 1 |
| 8 | Management of high blood pressure in children and adolescents: recommendations of the European Society of Hypertension显示文摘 | Empar Lurbe Renata Cifkova J Kennedy Cruickshank Michael J Dillon Isabel Ferreira Cecilia Invitti Tatiana Kuznetsova Stephane Laurent Giuseppe Mancia Francisco Morales-Olivas Wolfgang Rascher Josep Redon Franz Schaefer Tomas Seeman George Stergiou Elke Wü | 2009 | Journal of Hypertension2009，，9： | 1 |
| 9 | Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach显示文摘In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors. | Luigi D’Alfonso Francesco Giannini Giuseppe Franzè Giuseppe Fedele Francesco Pupo Giancarlo Fortino | 2024 | IEEE/CAA Journal of Automatica Sinica2024，11，1： | 0 |
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