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SSRN 2024年

作者： Cheng, Ting Liang, Yonghui Xu, Qimin Zhu, Shanying Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

In industrial sites, multiple real-time control systems often share computing resources. However, burst computing tasks may lead to the dropping of control computing subtasks, resulting in potential hazards. To address this issue, we propose a safety-aware task scheduling scheme. When burst computing tasks are triggered, this scheduling scheme adaptively releases resources from low-criticality control computing subtasks, ensuring the timely completion of burst computing tasks and keeping the control system state deviation within a safe threshold. To achieve the scheduling scheme, we propose an efficient algorithm called ADP-Opt. It decouples the complex original problem into multiple subproblems, which greatly reduces the search space and improves the solution efficiency. In the suboptimization problem, safety is maintained by limiting the upper bound of the system state's deviation to below the threshold. By introducing a penalty term in the cost function related to computing resources, we aim to balance the impact of control computing subtasks on control performance and the consumption of computing resources. Consequently, the overall cost of the control system can be minimized while releasing enough resources for burst computing tasks. Simulation results show that the scheduling decisions made by ADP-Opt can approach the optimal decision by approximately 99% efficiently. © 2024, The Authors. All rights reserved.

关键词： Cost functions

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Discrete-time inverse linear quadratic optimal control over fnite time-horizon under noisy output measurements

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control Theory and Technology 2021年第4期19卷 563-572页

作者： Han Zhang Yibei Li Xiaoming Hu Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Department of Mathematics KTH Royal Institute of Technology10044 StockholmSweden

In this paper,the problem of inverse quadratic optimal control over fnite time-horizon for discrete-time linear systems is *** goal is to recover the corresponding quadratic objective function using noisy ***,the identifability of the model structure for the inverse optimal control problem is analyzed under relative degree assumption and we show the model structure is strictly globally ***,we study the inverse optimal control problem whose initial state distribution and the observation noise distribution are unknown,yet the exact observations on the initial states are *** formulate the problem as a risk minimization problem and approximate the problem using empirical *** is further shown that the solution to the approximated problem is statistically consistent under the assumption of relative *** then study the case where the exact observations on the initial states are not available,yet the observation noises are known to be white Gaussian distributed and the distribution of the initial state is also Gaussian(with unknown mean and covariance).EM-algorithm is used to estimate the parameters in the objective *** efectiveness of our results are demonstrated by numerical examples.

关键词： Inverse optimal control Linear quadratic regulator Statistical consistency EM-algorithm

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Fully Circuit Implementation of a two-layer Memristive Neural Network for Pattern Recognition 11

Fully Circuit Implementation of a two-layer Memristive Neura...

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11th International Conference on Information Science and Technology, ICIST 2021

作者： Li, Mian Wang, Xiaoping Chen, Zhanfei Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China

ISBN: (纸本)9781665412667

In this paper, a fully circuit implementation of Memristive Neural Network (MNN) is proposed. The forward calculation of the network is based on winner-take-all (WTA) mechanism. The weight updating is achieved through the difference of pre-spike and post-spike, which is more close to the biological weight adjustment mechanism. The network is implemented in a full circuit without additional control units. The designed circuit consists of four modules. The memristive crossbar array module with one-memristor (1M) unit structure can effectively calculate the vector-matrix multiplication with only one step. The switch S is replaced by the transistor in the designed leaky-integrate-and-fire (LIF) module, which can control the integration and leakage of the membrane voltage and realize the lateral inhibition between output neurons. Connecting the integrated monostable trigger and the difference circuit, the post-spike generating module can output the required post-spike. The signal switch module realizes the switching of signals connected to memristors by using voltage-controlled switches. The combination of two modules validly realizes weight updating. The functions of four modules are verified separately. We performed a simulation experiment of 5×3 pixels image classification based on the designed circuit in PSPICE. The circuit output results and the high classification accuracy prove the circuit can be effectively applied in pattern recognition. The noise experiment shows the robustness of the designed circuit. © 2021 IEEE.

关键词： image classification

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Bearing-based Formation Tracking of Nonholonomic Agents in the Leader's Local Frame

Bearing-based Formation Tracking of Nonholonomic Agents in t...

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2021 China Automation Congress, CAC 2021

作者： Lv, Ke Yang, Ziwen Zhu, Shanying Wang, Lin Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9781665426473

This paper investigates the formation tracking control problem of nonholonomic agents in the leader's local frame, based on bearing measurements. Most of existing works on formation tracking are aimed at tracking a given formation in the global frame, which cannot meet the needs of many applications such as a fleet of cars driving on the highway. In this case, if the cars cannot keep a fixed formation in the leader's local frame, they may drive off the highway. Thus we propose an integrated approach consisting of a bearing-based estimator and a tracking controller, to track a given formation in the leader's local frame. In order to eliminate the estimation error in formation tracking, a persistently exciting leader is characterized by conditions. The stability of the integrated method is proved rigorously. Simulation results prove the effectiveness of the proposed approach. © 2021 IEEE

关键词： Integrated control

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Bearing-only Formation control of Nonholonomic Agents with Unknown Dynamic Leaders

Bearing-only Formation Control of Nonholonomic Agents with U...

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2021 China Automation Congress, CAC 2021

作者： Su, Haifan Yang, Ziwen Zhu, Shanying Chen, Cailian Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9781665426473

In this paper, the problem of bearing-only formation tracking control of multiple nonholonomic agents is studied. A leader-follower structure is adopted, where the leaders are moving at an unknown constant linear velocity and time-varying orientation. To solve the problem using bearing-only measurements, a finite-time estimator is firstly proposed to estimate the leaders' orientation information. Then, an adaptation law for estimating the leaders' linear velocity is proposed, based on which control inputs for tracking the leaders in a predefined bearing-based formation are designed, so that formation tracking can be achieved asymptotically. Rigorous theoretical analysis of the closed-loop system is given. It is proved that both the estimation errors and formation errors converge to zero under the connectivity of the communication graph and conditions for bearing rigidity. Numerical simulations are presented to testify the effectiveness of the proposed method. © 2021 IEEE

关键词： Closed loop systems

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Zero-Sum Game Based Secure Tracking control of UAV Against FDI Attacks Using Fixed-Time Convergent Reinforcement Learning

Zero-Sum Game Based Secure Tracking Control of UAV Against F...

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IEEE Conference on Decision and control

作者： Zhenyu Gong Feisheng Yang Dongrui Wu Research & Development Institute of Northwestern Polytechnical University in Shenzhen School of Automation Northwestern Polytechnical University Xi'an China Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial and Automation Huazhong University of Science and Technology Wuhan China

In this paper, a fixed-time convergent reinforcement learning (RL) algorithm is developed to realize the secure tracking control of the unmanned aerial vehicle (UAV) via the zero-sum game for the first time. To mitigate FDI attack on actuators that may cause the UAV to deviate from the reference trajectory, a zero-sum differential game framework is built in which the secure controller tries to minimize the common performance function, yet the attacker plays a contrary role. Obtaining the optimal secure tracking controller depends on solving the Hamilton-Jacobi-Isaacs (HJI) equation related to the zero-sum game. Therefore, a critic-only online RL algorithm is proposed that can converge in a fixed time interval, with the corresponding convergence proof provided. A simulation example is given to show the effectiveness of the raised method.

关键词：

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Pcda: Efficient Decision-Based Black-Box Attack for Point Clouds

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SSRN 2023年

作者： Liu, Lianguang Lv, Junting Li, Depeng Xu, Bingrong Chen, Chongyang Zeng, Zhigang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China School of Automatio Wuhan University of Technology Wuhan430074 China

Deep neural networks for 3D point clouds have shown significant progress in safety-critical applications. However, the robustness of these deep 3D models is insufficient-explored when faced with adversarial attacks. The existing point clouds attack methods usually rely on detailed model information (white-box attacks) or access to the training data (transfer-based black-box attacks). In this work, we make the first attempt in decision-based black-box attack for point clouds (PCDA), which only leverages the predicted labels of the victim models. Specifically, a novel perturbation projection based on chamfer distance is developed to be compatible with 3D irregular data, and the gradient estimation based on low-dimensional subspaces can generate smoother perturbations. Moreover, armed with iterative closest point, the novel perturbation initialization can improve the effectiveness of targeted black-box attacks. Evaluated on a variety of typical 3D models, our algorithm can efficiently generate smooth 3D adversarial samples with a lower magnitude of perturbations. © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

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Multi-Objective Optimal Configuration and Stable-Dynamic Management Rules of Grid-Connected Sofc/Lb Microgrids Accelerated by Energy-Based Pre-Selection

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SSRN 2024年

作者： Yin, Zishan Tang, Xiyun Wang, Zhuo Deng, Zhonghua Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Imaging Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China Wuhan Huamao Automation Co. Ltd. China

Microgrids are suitable to consume the increasing renewable sources to meet the fluctuating load demand nowadays, and configuration design is essential to build techno-economic microgrids. Solid Oxide Fuel Cell (SOFC) has high efficiency, high power output, and high fuel adaptability, which can be implemented as a controllable unit combined with an electrolyzer in hydrogen hybrid microgrids. However, the SOFC system’s slow load response should be considered due to SOFC’s complex dynamic characteristics. In this research, a grid-connected SOFC/lithium battery (LB) microgrid integrated photovoltaic and wind energy is constructed, and the LB complements the SOFC system’s slow load response. The stable-dynamic management rules are proposed, considering both SOFC’s tracking response and LB ‘s dynamic discharging and charging limitation to enhance LB’s cycle times. The minimal life cycle cost and minimal renewable energy (RS) curtailment rate are optimized by NSGA-II and the solving process is accelerated by an energy-based pre-selection method. An actual case is studied in one small region in China. The acceleration method is evaluated by comparison and the trade-off between two objectives is proved by the Pareto of the optimal solutions. To further analyze daytime management, we solve the optimal compromise solution by the fuzzy function and study the power dispatching of the typical days. © 2024, The Authors. All rights reserved.

关键词： Hydrogen

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Proactive Resilient Day-Ahead Unit Commitment with Cloud Computing Data Centers

Proactive Resilient Day-Ahead Unit Commitment with Cloud Com...

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作者： Liu, Shengwei Zhao, Tianyang Liu, Xuan Li, Yuanzheng Wang, Peng Energy and Electricity Research Center Jinan University Zhuhai China School of Artificial Intelligence and Automation Ministry of Education Key Laboratory of Image Processing and Intelligence Control Huazhong University of Science and Technology Wuhan China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

To enhance the resilience of power systems toward the temporal and spatial impacts caused by extreme weather events, e.g., hurricanes, the flexibility of cloud data centers (CDCs) is treated as a kind of efficient demand response. Since the workloads of CDCs have the shifting capacity between different locations and time slots, a day-ahead unit commitment problem including data centers is proposed to explore the integrated spatial and temporal flexibility of the workloads to its full extent through task migration. Considering the uncertainty of probability density functions, the line failure rates, workload arrival rates, power loads are integrated into an ambiguity set. The scheduling process of generators and CDCs is modeled as a two-stage distributionally robust optimization problem, which is reformulated as a large-scale deterministic mixed-integer linear programming problem and solved by the multicuts Benders decomposition method. The performance of the proposed scheduling strategy is tested in both the IEEE 24-bus RTS system and the three-area RTS-96 system. The results reveal that the method could mitigate the adverse impacts of hurricanes by enhancing the resilience of power systems and decreasing the dropping workloads of CDCs. © 1972-2012 IEEE.

关键词： Hurricanes

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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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