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Resilient control under Quantization and Denial-of-Service: Co-designing a Deadbeat controller and Transmission Protocol

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arXiv 2021年

作者： Liu, Wenjie Sun, Jian Wang, Gang Bullo, Francesco Chen, Jie State Key Lab of Intelligent Control and Decision of Complex Systems The School of Automation Beijing Institute of Technology Beijing100081 China State Key Lab of Intelligent Control and Decision of Complex Systems The School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China Department of Control Science and Engineering Tongji University Shanghai201804 China Mechanical Engineering Department The Center of Control Dynamical Systems and Computation UC Santa BarbaraCA93106-5070 United States

This paper is concerned with the problem of stabilizing continuous-time linear time-invariant systems subject to quantization and Denial-of-Service (DoS) attacks. In this context, two DoS-induced challenges emerge with the design of resilient encoding schemes, namely, the coupling between encoding strategies of different signals, and the synchronization between the encoder and decoder. To address these challenges, a novel structure that is equipped with a deadbeat controller as well as a delicate transmission protocol for the input and output channels, co-designed leveraging the controllab.lity index, is put forward. When both input and output channels are subject to DoS attacks and quantization, the proposed structure is shown able to decouple the encoding schemes for input, output, and estimated output signals. This property is further corroborated by designing encoding schemes as well as conditions that ensure exponential stability of the closed-loop system. On the other hand, when only the output channel is subject to network phenomenon, the proposed structure can achieve exponential stabilization without acknowledgment (ACK) signals, in contrast to existing ACK-based results. Finally, a numerical example is given to demonstrate the practical merits of the proposed approach as well as the theory. © 2021, CC BY.

关键词： Denial-of-service attack

A comprehensive rule based method for substation topology error identification

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Dianwang Jishu/Power System Technology 2012年第5期36卷 166-172页

作者： Wang, Jing Ge, Minhui Sun, Hongbin Li, Qingxin Wu, Wenchuan Guo, Qinglai Zhang, Boming State Key Lab. of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Tsinghua University Haidian District Beijing 100084 China East China Electric Power Dispatch and Control Sub-Center East China Grid Company Limited Huangpu District Shanghai 200002 China

A substation topology error identification method based on comprehensive rules, including rules in different spatial scales such as element level, bay level and voltage level as well as rules in time sequence, is presented. Utilizing the superiority in multi-source, redundancy and rapid measurement in the substation, the multi spatial scale relevant rules of element, bay and voltage level as well as multi time sequence rules are proposed, and concrete implementation approach for such a method is given. The proposed method can improve the ability to identify the topology error, especially ability to identify switches without analog measurement, thus more reliable topological structure can be provided to control centre to improve the reliability of state estimation for the whole power system. Results of simulation and practical application show that the proposed method is effective.

关键词： Topology

Data-driven Self-triggered control via Trajectory Prediction

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arXiv 2022年

作者： Liu, Wenjie Sun, Jian Wang, Gang Bullo, Francesco Chen, Jie The State Key Lab of Intelligent Control and Decision of Complex Systems The School of Automation Beijing Institute of Technology Beijing100081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The Mechanical Engineering Department The Center of Control Dynamical Systems and Computation UC Santa BarbaraCA93106-5070 United States The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Self-triggered control, a well-documented technique for reducing the communication overhead while ensuring desired system performance, is gaining increasing popularity. However, existing methods for self-triggered control require explicit system models that are assumed perfectly known a priori. An end-to-end control paradigm known as data-driven control learns control laws directly from data, and offers a competing alternative to the routine system identification-then-control method. In this context, the present paper puts forth data-driven self-triggered control schemes for unknown linear systems using data collected offline. Specifically, for output feedback control systems, a data-driven model predictive control (MPC) scheme is proposed, which computes a sequence of control inputs while generating a predicted system trajectory. A data-driven self-triggering law is designed using the predicted trajectory, to determine the next triggering time once a new measurement becomes availab.e. For state feedback control systems, instead of capitalizing on MPC to predict the trajectory, a data-fitting problem using the pre-collected input-state data is solved, whose solution is employed to construct the self-triggering mechanism. Both feasibility and stability are established for the proposed self-triggered controllers, which are validated using numerical examples. © 2022, CC BY.

关键词： Model predictive control

Power system state estimation via feasible point pursuit: Algorithms and Cramér-Rao bound

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arXiv 2017年

作者： Wang, Gang Zamzam, Ahmed S. Giannakis, Georgios B. Sidiropoulos, Nicholas D. Digital Tech. Center ECE Dept. U. of Minnesota MplsMN55455 United States State Key Lab. of Intelligent Control and Decision of Complex Systems Beijing Inst. of Tech. Beijing100081 China

Accurately monitoring the system's operating point is central to the reliable and economic operation of an electric power grid. Power system state estimation (PSSE) aims to obtain complete voltage magnitude and angle information at each bus given a number of system variables at selected buses and lines. Power flow analysis is a special case of PSSE, and amounts to solving a set of noise-free power flow equations. Physical laws dictate quadratic relationships between availab.e quantities and unknown voltages, rendering general instances of power flow and PSSE nonconvex and NP-hard. Past approaches are largely based on gradient-type iterative procedures or semidefinite relaxation (SDR). Due to nonconvexity, the solution obtained via gradienttype schemes depends on initialization, while SDR methods do not perform as desired in challenging scenarios. This paper puts forth novel feasible point pursuit (FPP)-based solvers for power flow and PSSE, which iteratively seek feasible solutions for a nonconvex quadratically constrained quadratic programming (QCQP) reformulation of the weighted least-squares (WLS) problem. Relative to the prior art, the developed solvers offer superior performance at the cost of higher complexity. Furthermore, they converge to a stationary point of the WLS problem. As a baseline for comparing different estimators, the Cramér-Rao lower bound (CRLB) is derived for the fundamental PSSE problem in this paper. Judicious numerical tests on several IEEE benchmark systems showcase markedly improved performance of our FPPbased solvers for both power flow and PSSE tasks over popular WLS-based Gauss-Newton iterations and SDR approaches. Copyright © 2017, The Authors. All rights reserved.

关键词： state estimation

Morphological characterization of Cu-W thin films based on wavelet transform

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Zhenkong Kexue yu Jishu Xuebao/Vacuum Science and Technology

Zhenkong Kexue yu Jishu Xuebao/Vacuum Science and Technology 2004年第SUPPL.期24卷 14-16+37页

作者： Wang, Yuan Bai, Xuanyu Xu, Kewei Fan, Duowang State-Key Laboratory for Mechanical Behavior of Materials Xi'an Jiaotong University Xi'an 710049 China Department of Mechanical Engineering Lanzhou Railway Institute Lanzhou 730070 China Lab. of Opto-Electronic Technology and Intelligent Control Lanzhou Jiaotong University Lanzhou 730070 China

The evolution of surface morphology of Cu-W thin films with deposition time on silicon wafers was studied by discrete wavelet transform (DWT). A strategy based on wavelet transform to describe surface morphology of thin films was presented. The results showed that the surface morphology of thin films was unstable until the sputtering time exceeds 10 min. The surface morphology variations of different thin films could be distinguished primarily by high frequency signals.

关键词： Thin films

Reinforcement learning for relation classification from noisy data

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arXiv 2018年

作者： Feng, Jun Huang, Minlie Zhao, Li Yang, Yang Zhu, Xiaoyan State Key Lab. of Intelligent Technology and Systems National Lab. for Information Science and Technology Dept. of Computer Science and Technology Tsinghua University Beijing100084 China Microsoft Research Asia College of Computer Science and Technology Zhejiang University

Existing relation classification methods that rely on distant supervision assume that a bag of sentences mentioning an entity pair are all describing a relation for the entity pair. Such methods, performing classification at the bag level, cannot identify the mapping between a relation and a sentence, and largely suffers from the noisy lab.ling problem. In this paper, we propose a novel model for relation classification at the sentence level from noisy data. The model has two modules: an instance selector and a relation classifier. The instance selector chooses high-quality sentences with reinforcement learning and feeds the selected sentences into the relation classifier, and the relation classifier makes sentencelevel prediction and provides rewards to the instance selector. The two modules are trained jointly to optimize the instance selection and relation classification processes. Experiment results show that our model can deal with the noise of data effectively and obtains better performance for relation classification at the sentence level. Copyright © 2018, The Authors. All rights reserved.

关键词： Reinforcement learning

Shared control for teleoperation enhanced by autonomous obstacle avoidance of robot manipulator

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Shared control for teleoperation enhanced by autonomous obst...

IEEE/RSJ International Conference on intelligent Robots and systems

作者： Xinyu Wang Chenguang Yang Hongbin Ma Long Cheng Centre for Robotics and Neural Systems Plymouth University Plymouth UK State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Ministry of Education South China University of Technology Guangzhou China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

In this paper, a human robot shared control strategy is developed and tested on a Baxter robot. Using the proposed method, the human operator only needs to consider the motion of the end-effector of the manipulator, while the manipulator will avoid obstacle by itself without sacrificing the end effector motion performance. An improved obstacle avoidance strategy based on the joint space redundancy of the manipulator is designed. A dimension reduction method is presented to solve the over defined problem of avoiding velocity to achieve a more efficient use of the redundancy. By employment of an artificial parallel system of the teleoperate manipulator and the task switching weighting factor, the proposed control method enable the robot restoring back to the commanded pose smoothly when the obstacle is removed. By implementing the dimension reduction method, the trajectory of each joint of the manipulator can be controlled at the same time to achieve the restoring task. Thus, the proposed control method can eliminate the impact of the obstacle on the remaining task. Satisfactory experiment results demonstrate the effectiveness of the proposed methods.

关键词： Manipulators Collision avoidance Robot kinematics Trajectory Kinematics Robot sensing systems

Multi-Destination Cooperative Task Offloading in Blockchain-Based Vehicular Edge Computing Networks

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Multi-Destination Cooperative Task Offloading in Blockchain-...

IEEE International Conference on Unmanned systems (ICUS)

作者： Ping Lang Daxin Tian Xuting Duan Jianshan Zhou State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China

As a novel computing paradigm, the Vehicular Edge Computing (VEC) network provides an additional avenue for onboard task execution for connected and automated vehicles (CAVs) in unmanned systems. In a VEC network, CAVs can offload tasks to different external servers for execution and obtain results. However, existing task offloading studies only focus on the one-to-one offloading of onboard tasks to edge servers, ignoring the requirements of parallel task execution and security. In this paper, we propose a blockchain-based multi-destination cooperative task offloading architecture in a VEC network. Based on this architecture, we analyze the task offloading and blockchain models and formulate a multi-destination cooperative task offloading optimization problem. Finally, we compare the performance of different multi-destination task offloading methods in simulations and demonstrate the effectiveness of the proposed architecture and optimization.

关键词：

Automatic hot event detection using both media and user attention

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Journal of Computational Information systems 2008年第3期4卷 985-992页

作者： Wang, Canhui Zhang, Min Ma, Shaoping Ru, Liyun State Key Lab. of Intelligent Technology and Systems CS and T Department Tsinghua University Beijing 100084 China Tsinghua National Laboratory for Information Science and Technology CS and T Department Tsinghua University Beijing 100084 China

Hot events reveal the society's attention and can help to watch the public voice or make decisions. Currently, hot events of various domains are provided by some organizations. Most of the results are considered to be generated manually, which are subjective though costing lots of human efforts. In this paper, a two-stage automatic algorithm for hot event detection is proposed. The first stage is event detection and tracking, in which news stories are organized into events accurately and effectively. The second stage is event ranking, in which both the media and user attention paid to events are taken into consideration. Top ranked events are returned as hot ones. Experiments performed on practical Web datasets show that: (1) F-measure of the best event detection and tracking results is close to 90%;(2) Hot events generated by the proposed algorithm reflect both the media and users' influence on the event ranking, which is considered to be more objective.

关键词： Event detection and tracking Hot event detection Media attention User attention