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Online adaptive Q-learning method for fully cooperative linear quadratic dynamic games

Science China(Information Sciences) 2019年第12期62卷 164-177页

作者： Xinxing LI Zhihong PENG Lei JIAO Lele XI Junqi CAI School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

A model-based offline policy iteration(PI) algorithm and a model-free online Q-learning algorithm are proposed for solving fully cooperative linear quadratic dynamic games. The PI-based adaptive Q-learning method can learn the feedback Nash equilibrium online using the state samples generated by behavior policies, without sending inquiries to the system model. Unlike the existing Q-learning methods, this novel Q-learning algorithm executes both policy evaluation and policy improvement in an adaptive *** prove the convergence of the offline PI algorithm by proving its equivalence to Newton's method while solving the game algebraic Riccati equation(GARE). Furthermore, we prove that the proposed Q-learning method will converge to the Nash equilibrium under a small learning rate if the method satisfies certain persistence of excitation conditions, which can be easily met by suitable behavior policies. Our simulation results demonstrate the good performance of the proposed online adaptive Q-learning algorithm.

关键词： adaptive dynamic programming reinforcement learning Q-learning fully cooperative linear quadratic dynamic games policy iteration off-policy

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Adaptive fault-tolerant controller design for airbreathing hypersonic vehicle with input saturation

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Journal of systems Engineering and Electronics 2013年第3期24卷 488-499页

作者： Haibin Sun Shihua Li Changyin Sun Key Laboratory of Measurement and Control of Complex Systems of Engineering(Ministry of Education) School of AutomationSoutheast University

The problem of fault-tolerant control is discussed for the longitudinal model of an airbreathing hypersonic vehicle （AHV） with actuator faults and external disturbances. Firstly, a fault-tolerant control strategy is presented for the longitudinal model of an AHV, which guarantees that velocity and altitude track their reference trajectories at an exponential convergence rate. However, this method needs to know the minimum value of the actuator efficiency factor and the upper bound of the external disturbances, which makes it not easy to implement. Then an improved adaptive fault-tolerant control scheme is proposed, where two adaptive laws are employed to estimate the upper bound of the external disturbances and the minimum value of the actuator efficiency factor, respectively. Secondly, the problem of designing a control scheme with control constraints is further considered, and a new adaptive fault-tolerant control strategy with input saturation is designed to guarantee that velocity and altitude track their reference trajectories. Finally, simulation results are given to show the effectiveness of the proposed methods.

关键词： airbreathing hypersonic vehicle （AHV） fault-tolerant control （FTC） adaptive control input saturation.

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Further results on cloud control systems

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Science China(Information Sciences) 2016年第7期59卷 232-236页

作者： Yuanqing XIA Yongming QIN Di-Hua ZHAI Senchun CHAI School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology

This paper is devoted to further investigating the cloud control systems(CCSs). The benefits and challenges of CCSs are provided. Both new research results of ours and some typical work made by other researchers are p... 详细信息

关键词： cloud control systems cloud computing cyber-physical systems networked control systems big data

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Integrated Communication and Learned Recognizer with Customized RIS Phases and Sensing Durations

arXiv

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arXiv 2025年

作者： Huang, Yixuan Yang, Jie Wen, Chao-Kai Jin, Shi National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan

Future wireless communication networks are expected to be smarter and more aware of their surroundings, enabling a wide range of context-aware applications. Reconfigurable intelligent surfaces (RISs) are set to play a critical role in supporting various sensing tasks, such as target recognition. However, current methods typically use RIS configurations optimized once and applied over fixed sensing durations, limiting their ability to adapt to different targets and reducing sensing accuracy. To overcome these limitations, this study proposes an advanced wireless communication system that multiplexes downlink signals for environmental sensing and introduces an intelligent recognizer powered by deep learning techniques. Specifically, we design a novel neural network based on the long short-term memory architecture and the physical channel model. This network iteratively captures and fuses information from previous measurements, adaptively customizing RIS phases to gather the most relevant information for the recognition task at subsequent moments. These configurations are dynamically adjusted according to scene, task, target, and quantization priors. Furthermore, the recognizer includes a decision-making module that dynamically allocates different sensing durations, determining whether to continue or terminate the sensing process based on the collected measurements. This approach maximizes resource utilization efficiency. Simulation results demonstrate that the proposed method significantly outperforms state-of-the-art techniques while minimizing the impact on communication performance, even when sensing and communication occur simultaneously. Part of the source code for this paper can be accessed at https://***/kiwi1944/CRISense. Copyright © 2025, The Authors. All rights reserved.

关键词： Long short-term memory

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Improved Stability Criteria on Discrete-time systems with Time-varying and Distributed Delays

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International Journal of Automation and computing 2013年第3期10卷 260-266页

作者： Ting Wang Ming-Xiang Xue Chun Zhang Shu-Min Fei Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University

This work was supported by National Natural Science Foun- dation of China （Nos. 60905009, 61004032, 61104119, 61174076, and 61172135）, and Jiangsu Province Natural Science Foundation （Nos. SBK201240801 and BK20123... 详细信息

关键词： Discrete-time system global stability interval time-varying delay distributed delay reciprocal convex technique.

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Adaptive-triggered H∞ sliding-mode optimal control for nonlinear input-limited systems

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Communications in Nonlinear Science and Numerical Simulation 2025年 149卷

作者： Zhang, Hongxu Wang, Honggui Department of Applied Mathematics Harbin University of Science and Technology Harbin150080 China Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology Harbin150080 China

This paper concentrates on the H∞ sliding mode optimal control (SMOC) problem for nonlinear systems with mismatched interference and constrained input. Firstly, an adaptive-triggered strategy for the discontinuous control part is employed, which can suppress input interference and the separated matched disturbances. Also, the system trajectories are guaranteed to converge to the sliding manifold. Moreover, the adaptive-triggered strategy is optimized into self-triggered strategy with the aim to avoid the real-time measurement of triggered conditions, and the minimum time interval is obtained to prevent Zeno phenomenon. Subsequently, the optimal H∞ control problem of sliding motion turns into a two-person ZS game issue. To derive the solutions of event-trigger HJI equation, an adaptive dynamic programming (ADP) algorithm with critic-only structure is implemented to obtain the optimal control online. Furthermore, by utilizing the Lyapunov technique, the uniformly ultimately bounded (UUB) conditions about system state and the weight estimation error are obtained. At last, simulation outcomes are analyzed to validate the effectiveness of the control strategy. © 2025 Elsevier B.V.

关键词： Sliding mode control

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Research on Temperature Error Calibration Method of Fluxgate Sensor

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Journal of Advanced Computational Intelligence and Intelligent Informatics 2025年第3期29卷 583-591页

作者： Yang, Ruiping Ge, Jian Luo, Wang Hu, Xiangyun She, Jinhua Chugo, Daisuke Dong, Haobin School of Automation China University of Geosciences No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education No 388 Lumo Road Hongshan District Hubei Wuhan430074 China School of Engineering Kwansai Gakuin University 1 Gakuen Uegahara Hyogo Sanda669-1330 Japan School of Geophysics and Geomatics China University of Geosciences No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Hubei Subsurface Multi-scale Imaging Key Laboratory No.388 Lumo Road Hongshan District Hubei Wuhan430074 China School of Engineering Tokyo University of Technology 1404-1 Katakuramachi Hachioji Tokyo192-0982 Japan

The fluxgate sensor is the most widely used sensor in vector magnetic measurement. However, during long-term continuous observation, the fluxgate sensor will produce large measurement errors due to changes in ambient temperature. This paper proposes a temperature calibration method for the fluxgate sensor based on polynomial fitting to address the temperature error of fluxgate sensors. First, the effect of temperature on the performance indicators of the fluxgate sensor was analyzed. Second, according to the existing temperature-magnetic field data, a temperature calibration model of the fluxgate sensor was constructed. Compared with other temperature calibration methods, the result shows that the proposed temperature calibration method is relatively simple and can better achieve real-time calibration for sensor application scenarios. Finally, to verify the effectiveness of the proposed method, numerous laboratory experiments were implemented. The temperature drift was reduced from about 700 nT before calibration to about 1 nT, root mean square error RMSE = 11.7189, indicating that the proposed method has a good temperature calibration effect on the data measured by the fluxgate sensor within the variable temperature background. © Fuji Technology Press Ltd.

关键词： Magnetic field measurement

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Adaptive control Based on Neural Networks for an Uncertain 2-DOF Helicopter System With Input Deadzone and Output Constraints

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IEEE/CAA Journal of Automatica Sinica 2019年第3期6卷 807-815页

作者： Yuncheng Ouyang Lu Dong Lei Xue Changyin Sun IEEE the School of Automation and the Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

In this paper, a study of control for an uncertain2-degree of freedom(DOF) helicopter system is given. The2-DOF helicopter is subject to input deadzone and output constraints. In order to cope with system uncertainties and input deadzone, the neural network technique is introduced because of its capability in approximation. In order to update the weights of the neural network, an adaptive control method is utilized to improve the system adaptability. Furthermore, the integral barrier Lyapunov function(IBLF) is adopt in control design to guarantee the condition of output constraints and boundedness of the corresponding tracking errors. The Lyapunov direct method is applied in the control design to analyze system stability and convergence. Finally, numerical simulations are conducted to prove the feasibility and effectiveness of the proposed control based on the model of Quanser's 2-DOF helicopter.

关键词： 2-degree of freedom (DOF) helicopter adaptive control input deadzone integral barrier Lyapunov function neural networks output constraints

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Unintended side effect of the coal-to-gas policy in North China Plain: Migration of the sources and health risks of ambient PAHs

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Science of the Total Environment 2025年 958卷 178050页

作者： Li, Zhiyong Liu, Chen Ren, Zhuangzhuang Liu, Jinming Ma, Xiaohua Ning, Zhi Meng, Jianwei Liu, Aiqin Ma, Huichun Wang, Lei Chen, Lan Wang, Hao Kong, Shaofei Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control Department of Environmental Science and Engineering North China Electric Power University Baoding071003 China MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environmental Science and Engineering North China Electric Power University Beijing102206 China Hebei Key Lab of Mineral Resources and Ecological Environment Monitoring Hebei Research Center for Geoanalysis Baoding071051 China Department of Atmospheric Sciences School of Environmental Sciences China University of Geosciences Wuhan430074 China

Ongoing coal-to-gas (CTG) largely cut down both coal consumption and associated PM2.5. However, a knowledge gap still existed in CTG impacts on the other energy and organic pollutant emissions. Coupling on-site investigation with statistical yearbooks, we provided a more realistic energy evolutions before (BCTG), during (DCTG), and after (ACTG) the CTG for Hebei Province. Together, we examined the impacts of CTG derived energy conversion on PM2.5-bound PAHs at urban (UA)/suburban rural (SRA)/remote rural (RRA) sites in winter 2022. As expected, the consumptions of coal and natural gas (NG) far decreased and increased from BCTG to ACTG, respectively. Accidentally, biomass usage rose by 60.7%, and rural CTG acted as a main driver. Specially, SRA's NG-shortage and coal-stove demolition should be the main inducements, and RRA's coal-sale ban was another trigger in the early stage of CTG. ∑18PAHs and ∑8TPAHs stand for the sum of 18 PAHs and 8 toxic PAHs, respectively. ∑18PAHs (ng/m3) presented as SRA (81.8) > RRA (46.4) > UA (19.4). Biomass burning (BB) and NG combustion (NGC) contributed most to∑18PAHs of 31.0% and 23.1% at SRA, resulting in the highest ∑18PAHs, ∑18PAHs/PM2.5, and ∑8TPAHs/PM2.5, and incremental lifetime cancer risk values. Also, NGC has become the second largest contributor at UA. Variations in both diagnostic ratios and source-depend isomers further proved the prominence of NGC related PAHs at UA vs. SRA. Notably, RRA was least affected by the CTG, coal combustion (CC, 40.4%) and BB (32.6%) still occupied the top positions. In short, CTG gave rise to an upsurge in biomass usage, and the incremental PAHs emissions from BB vs. NGC. This study underlined that the priorities should be given to rural NG guarantee and subsidy retention, and biomass prohibition for further air quality improvement. © 2024 Elsevier B.V.

关键词： Coal

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Load Prediction Model of Gas Boiler Generator Set Based on CNN-LSTM 11th

Load Prediction Model of Gas Boiler Generator Set Based on...

引用

11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： Xu, Yan Wu, Min Hu, Jie Peng, Fu-Sheng Zhang, Wen Song, Wen-Shuo Li, Hui-Hang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789819647521

With the proposal of carbon peak and carbon neutrality targets and the construction of a new power system, improving energy efficiency and reducing carbon emissions have become the key to the sustainable development of industrial boiler generator sets. However, the current load scheduling of gas boiler power plants is mainly based on manual experience, which limits achieving more efficient and stable operation. Accurate short-term load forecasting can help dispatchers to make reasonable production schedules. Therefore, this paper proposes a hybrid load forecasting model for generator sets based on convolutional neural networks combined with long short-term memory networks. First, the Isolation Forest algorithm eliminates anomalies in the historical data set. Then, variables related to unit load are selected by combining mechanistic analysis with the Spearman algorithm. Considering the multiple operating conditions and high complexity of unit loads, the CNN-LSTM network is used to fully extract the spatial and temporal characteristics to build the load prediction model. Finally, experiments are conducted using actual production data, showing that the proposed method is effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electric load dispatching

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