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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： He, Qianwei Wu, Hao Tang, Maoqin Liu, Lei Wang, Yongji Cheng, Zhongtao National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (纸本)9789811581540

For the strong nonlinearity and uncertainty in the ascent guidance problem of air-breathing hypersonic vehicle, an adaptive ascent guidance scheme based on model predictive static programming (MPSP) algorithm is investigated in this paper. The purpose of guidance scheme is to drive the vehicle to the desired terminal states under the disturbance and uncertain environment. Since MPSP algorithm is effective in solving terminal constrained optimal control problem, the guidance command is obtained to shape the ascent trajectory of the vehicle by this technique. Besides, considering that MPSP is a model-dependent algorithm that will be affected by the complex and changeable atmospheric environment, an extended Kalman filter (EKF) is adopted to identify the deviation of thrust coefficient, lift coefficient and drag coefficient online in a real flight condition, which can provide the adaptability of guidance scheme. Finally, the performance of the proposed guidance scheme in simulation proves that its effectiveness in flight missions. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hypersonic vehicles

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Attitude control of Reentry Vehicle Based on Adaptive Dynamic Programming with Incremental Model

Attitude Control of Reentry Vehicle Based on Adaptive Dynami...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Li, Xu Zheng, Zongzhun Liu, Lei Cheng, Zhongtao Wang, Yongji National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (纸本)9789811581540

Based on the incremental model, this paper investigates an adaptive dynamic programming (ADP) control scheme for reentry vehicles. First, the attitude dynamics of the reentry vehicle and its incremental form are established, then the ADP-based optimal controller is devised with reference to the dual heuristic dynamic programming (DHP) framework. Expediently, some local incremental parameters that the controller requires can be estimated through recursive least squares (RLS) technology online, replacing the model network that needs to be globally trained in advance in DHP. In addition, a target critic network is introduced to reduce the impact of state changes on the network parameters during the internal iterations of a time step, so it improves the learning stability. Finally, this control strategy is implemented to an attitude control system of the reentry vehicle, and online simulations verify its effectiveness. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Attitude control

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A Semisupervised Soft-Sensor of Just-in-Time Learning With Structure Entropy Clustering and Applications for Industrial Processes Monitoring

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 722-733页

作者： Li, Dong Liu, Yiqi Huang, Daoping Xu, Chong South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science and Engineering Guangzhou510640 China Technical University of Denmark Process and Systems Engineering Center Department of Chemical and Biochemical Engineering Lyngby2800 Denmark South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Gannan Normal University School of Physics and Electronic Information Ganzhou341000 China

To monitor industrial processes properly, soft-sensors are widely used to predict significant but difficult-to-measure quality variables. However, the prediction performances of traditional data-driven soft-sensors are usually unacceptable once suffering from high-nonlinear, high-dimension, and imblance data issues. Therefore, a semisupervised soft-sensor, which is learned by a just-in-time method with structure entropy clustering (SS-JITL-SEC), is proposed aiming to improve prediction performance with a simpler way. Inspired by a divide and conquer strategy, a novel SEC method is proposed to achieve several clusters and then to translate the highly complex and nonlinear modeling problems into simple and linear ones. Moreover, the training dataset is extended through a mixed SS labeling approach. Finally, dissimilarity-based JITL works together with the resulting clustering subdatasets to formulate a local adaptive prediction model. Two datasets from different types of wastewater treatment plants are used to verify the effectiveness of the proposed soft-sensor. The results show that the SS-JITL-SEC soft-sensor can achieve better prediction performance than other standard counterparts, and even for effective process monitoring with the resulted residuals. © 2020 IEEE.

关键词： Entropy

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Radar-Based Multi-Target Localization and Vital Sign Monitoring

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Journal of Computer and Communications 2024年第11期12卷 263-278页

作者： Yuping Shi Qinwei Li Hang Wu Ming Yu Tianjin Key Laboratory for Advanced Signal Processing School of Electronic Information and Automation Civil Aviation University of China Tianjin China Systems Engineering Institute Academy of Military Science People’s Liberation Army Tianjin China

The frequency-modulated continuous wave (FMCW) radar, known for its high range resolution, has garnered significant attention in the field of non-contact vital sign monitoring. However, accurately locating multiple targets and separating their vital sign signals remains a challenging research topic. This paper proposes a scene-differentiated method for multi-target localization and vital sign monitoring. The approach identifies the relative positions of multiple targets using Range FFT and determines the directions of targets via the multiple signal classification (MUSIC) algorithm. Phase signals within the range bins corresponding to the targets are separated using bandpass filtering. If multiple targets reside in the same range bin, the variational mode decomposition (VMD) algorithm is employed to decompose their breathing or heartbeat signals. Experimental results demonstrate that the proposed method accurately localizes targets. When multiple targets occupy the same range bin, the mean absolute error (MAE) for respiratory signals is 3 bpm, and the MAE for heartbeat signals is 5 bpm.

关键词： Frequency-Modulated Continuous Wave (FMCW) Radar Multi-Target Multiple Signal Classification (MUSIC) Variational Mode Decomposition (VMD)

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Unidentifiability of System Dynamics: Conditions and controller Design

arXiv

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arXiv 2023年

作者： Mao, Xiangyu He, Jianping The Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

How to make a dynamic system unidentifiable is an important but still open issue. It not only requires that the parameters of the systems but also the equivalent systems cannot be identified by any identification approaches. Thus, it is a much more challenging problem than the existing analysis of parameter identifiability. In this paper, we investigate the problem of dynamic unidentifiability and design the controller to make the system dynamics unidentifiable. Specifically, we first define dynamic unidentifiability by taking both system parameters and equivalent systems into consideration. Then, we obtain the necessary and sufficient condition for unidentifiability based on the Fisher information Matrix. This condition is derived by analysis of the relationship between the unidentifiable parameters and the Hessian matrix of the system function. Next, we propose a controller design scheme for ensuring dynamic unidentifiability under linear system models. We prove that for controllable and observable linear time-invariant systems, the requirement of unidentifiability is equivalent to the requirement of a low-rank controller. Then, the low-rank controller design problem is solved by transforming it into a model order reduction problem. We demonstrate the effectiveness of our method by simulation. Copyright © 2023, The Authors. All rights reserved.

关键词： controllers

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Resilient Event-Triggered Model Predictive control for Adaptive Cruise control Under Sensor Attacks

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 807-809页

作者： Zhijian Hu Rong Su Kai Zhang Zeyuan Xu Renjie Ma School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore Key Laboratory of Ultra-Precision Intelligent Instrumentation Ministry of Industry and Information Technologyand the Center of Ultra-Precision Optoelectronic Instrument EngineeringHarbin Institute of TechnologyHarbin 150001China Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China Department of Chemical and Biomolecular Engineering National University of SingaporeSingapore 117585Singapore State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150001China IEEE

Dear Editor,This letter addresses the resilient model predictive control(MPC)problems for adaptive cruise control(ACC)systems under sensor *** the light of vulnerabilities of ACC systems to sensor attacks,an intrusion detection mechanism is proposed at the controller side to distinguish abnormal ***,the robust control gains are derived to design the terminal region constraint for MPC.

关键词： Trigger Event constraint

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Realizing submeter spatial resolution for Raman distributed fiber-optic sensing using a chaotic asymmetric paired-pulse correlation-enhanced scheme

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Photonics Research 2024年第10期12卷 2365-2375页

作者： BOWEN FAN JIAN LI ZIJIA CHENG XIAOHUI XUE MINGJIANG ZHANG College of Electronic Information and Optical Engineering Taiyuan University of TechnologyTaiyuan 030024China Key Laboratory of Advanced Transducers and Intelligent Control Systems(Ministry of Education and Shanxi Province) Taiyuan University of TechnologyTaiyuan 030024China College of Physics Taiyuan University of TechnologyTaiyuan 030024China

The sensing spatial resolution and signal-to-noise ratio(SNR)of Raman distributed optical fiber sensors are limited by the pulse width and weak Raman scattering ***,the sensing spatial resolution cannot exceed the order of meters at several kilometers sensing *** break through this physical bottleneck,a novel,to our knowledge,Raman scattering model based on paired-pulse sensing is *** fundamental origins of the observed limited spatial resolution of conventional schemes are analyzed,and a chaotic asymmetric paired-pulse correlation-enhanced scheme for Raman distributed fiber-optic sensing is proposed and experimentally *** proposed scheme uses a chaotic asymmetric paired-pulse as the sensing signal and extracts the light intensity information of each data point of the sensing fiber,which carries the random undulation characteristics of chaotic time series,based on the time-domain differential reconstruction *** scheme overcomes the pulse width limitation of spatial resolution via correlation and demodulation,enhances the correlation characteristics between the temperature-modulated Raman scattered light field and detection signal,and improves the ***,a sensing performance of 10 km,a spatial resolution of 30 cm,and an SNR of 6.67 dB are realized in the *** scheme provides a new research idea for a high-performance Raman distributed optical fiber sensing system.

关键词： fiber pulse scattering

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OPTIMAL MIXED STRATEGIES TO THE ZERO-SUM LINEAR DIFFERENTIAL GAME

arXiv

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arXiv 2023年

作者： Xu, Tao Xi, Wang He, Jianping Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

This paper exploits the weak approximation method to study a zero-sum linear differential game under mixed strategies. The stochastic nature of mixed strategies poses challenges in evaluating the game value and deriving the optimal strategies. To overcome these challenges, we first define the mixed strategy based on time discretization given the control period δ. Then, we design a stochastic differential equation (SDE) to approximate the discretized game dynamic with a small approximation error of scale O(δ2) in the weak sense. Moreover, we prove that the game payoff is also approximated in the same order of accuracy. Next, we solve the optimal mixed strategies and game values for the linear quadratic differential games. The effect of the control period is explicitly analyzed when the payoff is a terminal cost. Our results provide the first implementable form of the optimal mixed strategies for a zero-sum linear differential game. Finally, we provide numerical examples to illustrate and elaborate on our results. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

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Reinforcement Learning with Hierarchical Graph Structure for Flexible Job Shop Scheduling

Reinforcement Learning with Hierarchical Graph Structure for...

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

作者： Linli Zhang Dewei Li dept. of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

The flexible job shop scheduling problem (FJSP) is a NP-hard combinatorial optimization challenge, having extensive real-world industrial applications. For a given instance of FJSP, a scheduling solution need to be devised, which entails determining the appropriate machine for each operation and establishing the sequence in which operations are processed on a given machine, all while adhering to certain constraints. However, many of the methods are lacking in flexibility, unable to cope effectively with multi-relational operations and machine selection scenarios. This can make the representation of state and action challenging in practice, leading to a significant increase in decision complexity. This paper considers these issues by a hierarchical graph structure with a model that synergistically integrates two modules: the environment and the decision module. The environment module is characterized by a hierarchical graph neural network which defines the multi-relational FJSP instance where all machine and operation data are stored. The decision module incorporates the Actor-Critic networks, designed to train reasoning strategies and enhance decision performance, based on the states and rewards provided at each step by the environment module. The objective is to derive optimal scheduling strategies through interactions between the decision agent and the environment, targeting the minimum resources consumed or makespan. Numerical simulations validate the efficacy of the proposed approach, showing its potential to yield superior results and thereby enhance performance.

关键词：

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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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