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SSRN 2023年

作者： Wang, Zhenchun Wang, Nianguo School of Electrical Engineering Yanshan University Qinhuangdao066004 China Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China

This paper investigates the model predictive control (MPC) of a point-absorption sea wave energy converter (WEC). The dynamic model and information about upcoming waves serve as the foundation for MPC implementation, but building the plant model and forecasting waves will invariably introduce errors. As a result of this fact and the multi-step predictive optimization feature of MPC, a novel objective function based on the weighting factor is adopted in the MPC design, which has the following benefits: First, the weighting factor penalizes the objective function with errors at various steps in time, which can limit the adverse effects of uncertainties on the controller. Second, the weighting factor can better constrain the float displacement, ensuring the device’s safe operation. In addition, the weighting factor is optimized offline using a genetic algorithm, and its value changes depending on the sea state. The simulation results show the effectiveness of the proposed MPC strategy. © 2023, The Authors. All rights reserved.

关键词： Model predictive control

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A Novel A-ESO Composited Non-Recursive control Methodology for Complex High-Order Disturbed Nonlinear Systems

A Novel A-ESO Composited Non-Recursive Control Methodology f...

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Chinese control Conference (CCC)

作者： Cong Zhang Shiji Liu Shuang Liu School of Electrical Engineering Yanshan University Qinhuangdao Hebei China Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao Hebei China

This paper mainly focuses on a disturbance rejection control methodology for a series of mismatched and matched disturbed complex systems. Firstly, a novel finite-time arbitrary-order extended state observer (A-ESO) is proposed to accurately estimate the system states, disturbances, and their corresponding order derivatives. And then, a novel concise nonrecursive control ideology utilizing all the estimations of A-ESO is proposed to strictly guarantee finite-time stability and convergence of the whole closed-loop system. Significantly, compared with the existing nonrecursive control methods, the essential characteristic is that all the estimation information is utilized to construct the composite controller. This will be tremendously conducive to cost-saving and promoting practical implementations.

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Energy Efficiency Maximization for Hybrid Access Femtocell Networks via Incentive Mechanism and Power control Strategy

Energy Efficiency Maximization for Hybrid Access Femtocell N...

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IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Xuelin Liu Weimin Wang Zhixin Liu School of control science and engineering Dalian University of Technology Dalian China School of electrical engineering Yanshan University Qinhuangdao China Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao Hebei Province China

Femtocell network has a great development space in increasing coverage and capacity of wireless network. In order to meet the quality of service (QoS) requirements of MUEs in MBS coverage, we propose a seed channel incentive mechanism in the two-tier femtocell network, where the MBS provides sub-channels to FBSs to motivate them to serve for the MUEs within the MBS coverage. To maximize the energy efficiency of femtocell layer after hybrid access, the optimization problem is modeled. The combined method of worst-case, Dinkelbach and continuous convex approximation is developed to make the optimization problem solvable. In addition, in order to realize the practical application of the proposed scheme, an optimization algorithm combining sub-channel and power allocation is developed. The numerical results show that the proposed algorithm is effective in improving the energy efficiency of the femtocell layer.

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DexRepNet: Learning Dexterous Robotic Grasping Network with Geometric and Spatial Hand-Object Representations

DexRepNet: Learning Dexterous Robotic Grasping Network with ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Qingtao Liu Yu Cui Qi Ye Zhengnan Sun Haoming Li Gaofeng Li Lin Shao Jiming Chen College of Control Science and Engineering Zhejiang University Hangzhou China Key Lab of CS&AUS Zhejiang Province College of Control Science and Engineering and the State Key Laboratory of Industrial Control Technology Zhejiang University Department of Computer Science National University of Singapore Singapore

Robotic dexterous grasping is a challenging problem due to the high degree of freedom (DoF) and complex contacts of multi-fingered robotic hands. Existing deep re-inforcement learning (DRL) based methods leverage human demonstrations to reduce sample complexity due to the high dimensional action space with dexterous grasping. However, less attention has been paid to hand-object interaction representations for high-level generalization. In this paper, we propose a novel geometric and spatial hand-object interaction representation, named DexRep, to capture object surface features and the spatial relations between hands and objects during grasping. DexRep comprises Occupancy Feature for rough shapes within sensing range by moving hands, Surface Feature for changing hand-object surface distances, and LocalGeo Feature for local geometric surface features most related to potential contacts. Based on the new representation, we propose a dexterous deep reinforcement learning method DexRepNet to learn a generalizable grasping policy. Experimental results show that our method outperforms baselines using existing representations for robotic grasping dramatically both in grasp success rate and convergence speed. It achieves a 93% grasping success rate on seen objects and higher than 80% grasping success rates on diverse objects of unseen categories in both simulation and real-world experiments.

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case 63

Optimal Linear Deception Attacks on Remote State Estimation ...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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A Ship Power Sharing Strategy Based on Shapley Value Method and Cartel Mechanism

A Ship Power Sharing Strategy Based on Shapley Value Method ...

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Complex Systems and Intelligent Science (CSIS-IAC), International Annual Conference on

作者： Zhengxu Zhang Jie Yang Kai Ma Shiliang Guo Hui Li School of Electrical Engineering Yanshan University Qinhuangdao China Key Laboratory of Power Electronics for Energy Conservation and Drive Control of Hebei Province Yanshan University Qinhuangdao China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Key Laboratory of Intelligent Control and Neural Information Processing of the Ministry of Education Yanshan University Qinhuangdao China

ISBN: (数字)9798331504755

ISBN: (纸本)9798331504762

With the development of the maritime industry, the number and capacity of existing port cold-ironing (CI) equipment can no longer meet the power demand of ships during berthing, resulting in significant carbon emissions from ships within the port area. Therefore, a ship power sharing strategy based on Shapley value method and Cartel mechanism is proposed. Firstly, the rolling optimization model of ship power scheduling is established to adjust the ship power scheduling strategy according to the real-time information. Secondly, the cooperative game model of ship power sharing is established, and the cost sharing among cooperative ships is realized by Shapley value method. Finally, in order to reduce the situation that ships increase their own profits by deviating from cooperation and affect the overall profits, this paper introduces Cartel mechanism to punish the behavior of deviating from cooperation. The simulation results show that the power sharing strategy proposed in this paper can reduce the total ship cost and carbon emission by 5.28% and 3.78%, respectively. The introduction of Cartel mechanism can increase the cost of non-cooperative behavior, thus ensuring that all ships take cooperative behavior. The power sharing strategy based on Shapley method and Cartel mechanism proposed in this paper is helpful to the construction of green ports.

关键词： Costs Job shop scheduling Optimization models Simulation Carbon dioxide Microgrids Games Seaports Real-time systems Marine vehicles

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DPF-SLAM: Dense semantic SLAM based on dynamic probability fusion in dynamic environments

DPF-SLAM: Dense semantic SLAM based on dynamic probability f...

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2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022

作者： Liu, Xin Wen, Shuhuan Yuan, Mingxing Li, Pengjiang Zhao, Yongjie Manfredi, Luigi Yanshan University Eng. Res. Ctr. of the Ministry of Education for Intelligent Control System and Intelligent Equipment Key Laboratory of Industrial Computer Control Engineering of Hebei Province Qinhuangdao China Nankai University School of Artificial Intelligence China University of Dundee United Kingdom

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

With the development of simultaneous localization and mapping (SLAM) technology, Dynamic SLAM has been a challenging research topic. This paper presents a dynamic probability fusion SLAM (DPF-SLAM) algorithm, which adds a semantic segmentation thread and a dense reconstruction thread to ORB-SLAM2. We integrate dynamic prior probability obtained by semantic segmentation with dynamic probability obtained by dynamic point detection, which can decrease the effect of dynamic objects on the localization accuracy and meanwhile achieve the dense reconstruction of a static background. We evaluate DPF-SLAM system on the public TUM RGBD dataset. The experimental results show that the proposed algorithm has better localization accuracy than DS-SLAM and ORB-SLAM2, which are two relatively new algorithms in this area, and can obtain a good dense reconstruction effect. Moreover, through the performance comparison with our previous work, it is found that the algorithm speed and positioning accuracy are improved. © 2022 IEEE.

关键词： Semantics

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Distributed Fault-Tolerant Secondary control For Dc Microgrids Against False Data Injection Attacks

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SSRN 2022年

作者： Xie, Zongkui Wu, Zhongqiang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China

This paper focuses on the issue of unknown false data injection attacks (FDIA) of controllers in DC microgrid, and proposes a distributed fault-tolerant secondary controller for DC microgrid to ensure that the control objectives of voltage regulation and current sharing can be achieved when the system is subject to FDIA. Firstly, the secondary control problem in DC microgrid with FDIA is transformed into a first-order leader-following multi-agent system fault-tolerant consensus problem, and the impact of FDIA signals on the microgrid system is analyzed. Then, a distributed extended state observer (DESO) is designed based on the derived multi-agent system, which observes the injected FDIA signals using the relative output error of each distributed generators and its neighbours. Further, based on the observed FDIA signals, a fault-tolerant secondary controller is designed to eliminate the adverse effects of the attack signals on the system. Particularly, the stability analyses for the designed DESO and secondary controller prove that the control system is global asymptotically stable. Finally, the effectiveness and superiority of the proposed fault-tolerant secondary control method for DC microgrids with FDIA are verified by simulation analyses of four cases. © 2022, The Authors. All rights reserved.

关键词： Network security

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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel State Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

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A Speech Cryptosystem Using the New Chaotic System with a Capsule-Shaped Equilibrium Curve

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computers, Materials & Continua 2023年第6期75卷 5987-6006页

作者： Mohamad Afendee Mohamed Talal Bonny Aceng Sambas Sundarapandian Vaidyanathan Wafaa Al Nassan Sen Zhang Khaled Obaideen Mustafa Mamat Mohd Kamal Mohd Nawawi Faculty of Informatics and Computing Universiti Sultan Zainal AbidinMalaysia Department of Computer Engineering University of SharjahSharjah26666UAE Department of Mechanical Engineering Universitas Muhammadiyah TasikmalayaIndonesia Research and Development Centre Vel Tech UniversityAvadiChennaiIndia School of Artificial Intelligence and Automationand Key Laboratory of Image Processingand Intelligent Control of Education Ministry of ChinaHuazhong University of Scienceand TechnologyWuhan430074China Institute of Strategic Industrial Decision Modeling School of Quantitative SciencesUniversiti Utara Malaysia06010UUM SintokKedahMalaysia

In recent years,there are numerous studies on chaotic systems with special equilibrium curves having various shapes such as circle,butterfly,heart and *** paper describes a new 3-D chaotic dynamical system with a capsule-shaped equilibrium *** proposed chaotic system has two quadratic,two cubic and two quartic nonlinear *** is noted that the proposed chaotic system has a hidden attractor since it has an infinite number of equilibrium *** is also established that the proposed chaotic system exhibits multi-stability with two coexisting chaotic attractors for the same parameter values but differential initial states.A detailed bifurcation analysis with respect to variations in the system parameters is portrayed for the new chaotic system with capsule equilibrium *** have shown MATLAB plots to illustrate the capsule equilibrium curve,phase orbits of the new chaotic system,bifurcation diagrams and *** an engineering application,we have proposed a speech cryptosystem with a numerical algorithm,which is based on our novel 3-D chaotic system with a capsule-shaped equilibrium *** proposed speech cryptosystem follows its security evolution and implementation on Field Programmable Gate Array(FPGA)*** results show that the proposed encryption system utilizes 33%of the FPGA,while the maximum clock frequency is 178.28 MHz.

关键词： Chaos chaotic systems hidden attractors multi-stability bifurcation speech cryptosystem FPGA design

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