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42nd Chinese control Conference, CCC 2023

作者： Tang, Xiangyu Yu, Jianglong Peng, Siting Dong, Xiwang Li, Qingdong Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9789887581543

This paper studies the impact angle control guidance problem with general field-of-view (FOV) constraints for a moving target. Firstly, the control Lyapunov function (CLF) is constructed based on the state-dependent Riccati equation (SDRE) technique, and a nominal controller is designed to intercept the moving target at the desired impact angle without FOV constraints. The control barrier functions (CBFs) are designed according to the FOV constraints. Secondly, the CLF that guarantees stability is combined with the CBFs that guarantee forward invariance of the constraint sets. The minimum modification framework is used to numerically solve the guidance command through quadratic programming to ensure that the look angle of the missile always remains within the constraint interval during the interception process. Finally, the effectiveness of the proposed guidance law is verified by numerical examples. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Electronic guidance systems

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Improved Auction Algorithm for Weapon Target Assignment with Firepower-Health Model 42

Improved Auction Algorithm for Weapon Target Assignment with...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Shuobo Heng, Yong Hua, Yongzhao Dong, Xiwang Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Institute of Electronic System Engineering Beijing100854 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789887581543

This paper proposes an improved auction algorithm to optimize the efficiency of dynamic weapon target assignment (WTA) problem. Firstly, the dynamic battlefield environment of firepower-health model is analyzed and the constraints of weapon assignment problem are established. The firepower-health model is about the idea of adding constraints of weapon firepower and target health to promote the result of assignment more effectively. Secondly, in order to improve the computing speed of WTA algorithm, the penalty mechanism is introduced in the compensation auction algorithm. The main idea of improved algorithm is to reduce the extra consuming of the weapon during the assignment, from which penalty mechanism can optimize the assignment results and reduce the number of algorithm iterations by punishing the overkilled target under certain rules. Finally, the simulation results based on the dynamic firepower-health model show that the proposed algorithm can meet the requirements of firepower allocation, and can promote the effectiveness of assignment with high real-time response. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Dynamics

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PVTimesNet: A Hybrid Deep Learning Method for Enhancing Ultra-short-term PV Power Forecasting

PVTimesNet: A Hybrid Deep Learning Method for Enhancing Ultr...

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2024 China automation Congress, CAC 2024

作者： Wu, Ji Wang, Kai Ma, Wenwen Zhang, Jingxin Wang, Shibo China Electric Power Research Institute Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (纸本)9798350368604

Accurate ultra-short-term photovoltaic (PV) power forecasting is crucial for the real-time scheduling of grid systems. However, the inherent variability of solar energy makes this task extremely challenging. To enhance PV power forecasting, this paper introduces a novel hybrid model named PVTimesNet, designed to harness the strengths of Convolutional Neural Network (CNN) and Long Short-Term Memory Network (LSTM) for effective feature extraction. PVTimesNet consists of two parallel branches: the CNN1d branch, which captures correlations between multiple variables and adjacent time steps, and the LSTM branch, which learns the temporal dependencies within the PV power sequences. The features extracted by both branches are then concatenated and passed through a fully connected layer to generate multi-step PV power forecasts. Experimental results demonstrate that for forecast horizons of 1 to 4 hours, the proposed model significantly outperforms individual models and other CNN-LSTM hybrid structures. Additionally, it exhibits superior performance compared to related methods for longer forecast horizons. © 2024 IEEE.

关键词： Hybrid power

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A Novel Hybrid Transformer-Based Framework for Solar Irradiance Forecasting under Incomplete Data Scenarios

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IEEE Transactions on Industrial Informatics 2024年第6期20卷 8605-8615页

作者： Zhang, Hanjin Li, Bin Su, Shun-Feng Yang, Wankou Xie, Liping Southeast University School of Economics and Management Nanjing210096 China National Taiwan University of Science and Technology Department of Electrical Engineering Taipei106 Taiwan Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518063 China

Accurate prediction of solar irradiance is crucial for the effective utilization of solar energy. However, in real-world scenarios, complex irradiance patterns and prevalent incomplete data pose challenges to precise forecasting, resulting in additional uncertainties and instability. To address these issues, this study proposes a novel irradiance forecasting model that integrates a Mask-Transformer data imputation module and a prediction module centered around the typical patterns representation mechanism. The Mask-Transformer leverages a mask modeling mechanism to model the context of missing data, facilitating accurate estimation of missing values and reducing noise and uncertainty in the input data. The typical patterns representation mechanism comprises a series decomposition module and a feature fusion module, providing the module with the capability to mitigate nonlinearity and nonstationarity in solar irradiance data. This enhancement leads to improved short-term forecasting performance while maintaining long-term forecasting capabilities. Experimental results on two datasets demonstrate that the proposed model exhibits sufficient robustness and accuracy, making it effective in scenarios with incomplete data. © 2005-2012 IEEE.

关键词： Forecasting

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AI4S Based on DeSci: Reference Model and Research Issues

AI4S Based on DeSci: Reference Model and Research Issues

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Ding, Wenwen Li, Juanjuan Qin, Rui Guan, Sangtian Wang, Fei-Yue Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Macau University of Science and Technology Faculty of Innovation Engineering Macau China Institute of Automation The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350337020

The rise of Artificial Intelligence for Science (AI4S) has highlighted the importance and urgency of ensuring open-ness, fairness, impartiality, diversity, and sustainability in scientific systems. Existing scientific systems, referred to as Centralized Science (CeSci), are built on centralized organizational structures and top-down institutional frameworks, which are lagging behind the development and practical requirements of AI4S. To address these limitations, AI4S needs to embrace a new scientific organizational and operational paradigm, namely Decentralized Science (DeSci). It can provide strong support to AI4S via effectively addressing issues such as information silos, biases, unfair distribution, and monopolies and promoting multidisciplinary, interdisciplinary, and trans disciplinary cooperation in science. Based on these considerations, this paper presents the framework of AI4S based on DeSci and explores its potential application scenarios and research issues. The research can provide effective guidance for the development of scientific systems. © 2023 IEEE.

关键词： Artificial Intelligence for Science (AI4S) ChatGPT Decentralized Autonomous Organizations and Operations (DAOs) Decentralized Science (De-Sci) Generative Artificial Intelligence (GAI) Intelligent Science

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Novel vision-LiDAR fusion framework for human action recognition based on dynamic lateral connection

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IET Cyber-Systems and Robotics 2024年第4期6卷 21-31页

作者： Fei Yan Guangyao Jin Zheng Mu Shouxing Zhang Yinghao Cai Tao Lu Yan Zhuang The School of Control Science and Engineering Dalian University of TechnologyDalianChina Technology Centre of Dalian Customs Dalian CustomsDalianChina ZX‐YZ School of Network Science Haikou University of EconomicsHainanChina The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijingChina

In the past decades,substantial progress has been made in human action ***,most existing studies and datasets for human action recognition utilise still images or videos as the primary ***-based approaches can be easily impacted by adverse environmental *** this paper,the authors propose combining RGB images and point clouds from LiDAR sensors for human action recognition.A dynamic lateral convolutional network(DLCN)is proposed to fuse features from *** RGB features and the geometric information from the point clouds closely interact with each other in the DLCN,which is complementary in action *** experimental results on the JRDB-Act dataset demonstrate that the proposed DLCN outperforms the state-of-the-art approaches of human action *** authors show the potential of the proposed DLCN in various complex scenarios,which is highly valuable in real-world applications.

关键词： neural network-based pedestrian identification sensor fusion

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Cooperative Differential Games Guidance Laws for Multiple Missiles Against an Active Defense Target with Multiple Defenders

Cooperative Differential Games Guidance Laws for Multiple M...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Kang, Yangrui Yu, Jianglong Dong, Xiwang Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

In the scenario that multiple missiles intercept one active defense target with multiple defenders. The missiles aim to finish the tasks that intercept the target from different directions to achieve saturation and evade from the defenders at the same time and each defender aim at different missile. Different from the existing results, multiple defenders are concerned in the scenario. Firstly, the guidance problem is separated into two decoupled part which is missiles-target (MT) problem and missile-defender (MD) problem. Secondly, the linearized kinematics of MD and MT model is established. Thirdly, the guidance problem is transformed into a bilateral optimal problem and the guidance laws is obtained by solving the Hamilton function. Finally, numerical simulation is given to verify the correctness of the acquired theories. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Game theory

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Research on Sensorless control of Pulse Generator based on Sliding Mode Observer

Research on Sensorless Control of Pulse Generator based on S...

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2023 International Conference on Artificial Intelligence and automation control, AIAC 2023

作者： Zhang, Hui Wu, Zhiguo Jin, Bopi Yang, Shengxuan Yin, Guoliang Shenyang Jianzhu University College of Electrical and Control Engineering Shenyang China College of Electrical and Control Engineering Shenyang Jianzhu University State Key Laboratory of Robotics Shenyang Institute of Automation Institutes of Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Institutes of Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China

ISBN: (纸本)9798350383805

To address the problems of chattering and slow response in the sliding mode control system of surface-mounted permanent magnet synchronous motor (SPMSM), a novel sliding mode controller combined with an enhanced sliding mode observer is proposed. A new reaching law of sliding mode is designed, which uses the tanh function as the switching function of the control system to smooth the switching process. The terminal attractor is introduced to improve the convergence speed and control quality of the system. An improved sliding mode observer is developed, which replaces the sign function with a continuous function, compensates for the observation error, reduces the chattering effect, and improves the observation accuracy. A simulation model of double closed-loop speed control system based on the proposed sliding mode controller and observer is established, and a simulation experiment is conducted to compare it with the PI control system and the sliding mode control system based on exponential reaching law. The simulation results show that the proposed control strategy can effectively diminish the chattering effect, enhance the system convergence, and better track the given signal. © 2023 IEEE.

关键词： Sliding mode control

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Logarithmic Sliding-Mode control for High-Precision Rigid-Body Attitude Tracking 49

Logarithmic Sliding-Mode Control for High-Precision Rigid-Bo...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Dong, Hanlin Yang, Xuebo Chen, Zhongbo Liu, Xiyao School of Automation Northwestern Polytechnical University Xi'an China Research Institute of Intelligent Control Systems Harbin Institute of Technology Harbin China College of Control Science and Engineering Bohai University Jinzhou China Northwestern Polytechnical University Research Center for Intelligent Robotics Xi'an China

ISBN: (纸本)9798350331820

The problem of high-precision attitude tracking is studied in this paper under model uncertainty and external disturbance risk. First of all, the kinematics and dynamics model of rigid body is derived based on the quaternion theory. Then, a standard logarithmic sliding-mode function is constructed using the attitude quaternion and its derivatives of the rigid spacecraft, and the corresponding logarithmic sliding-mode controller is also derived. Finally, the stability of the controlled closed-loop system is demonstrated. Consistenting with theoretical proof, the numerical simulation results showed that the controlled rigid body can quickly track its desired attitude command, even if there are model uncertainty and external disturbance risks. © 2023 IEEE.

关键词： Disturbance rejection

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Formation Optimization Method of Multiple Hypersonic Vehicles

Formation Optimization Method of Multiple Hypersonic Vehicl...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Zhang, Yuqing Yu, Jianglong Dong, Xiwang Li, Qingdong Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

This paper constructed a collaborative combat effectiveness evaluation system with considering the characteristics and limitations of the vehicles. Firstly, multiple hypersonic vehicles formation problem is converted to an optimization problem based on the collaborative combat effectiveness evaluation system. Secondly, the relative distance and angles between vehicle and a certain reference point is selected as the formation parameters, which are chosen as optimization variables in the optimization algorithm. Thirdly, the efficiency function corresponding to each evaluation indicator is given under the constraints of the vehicle and the PSACO (particle swarm ant colony optimization) algorithm is used to solving this optimization problem. In particular, the scenario of detection and the scenario of penetration are designed respectively considering different combat requirements. Finally, it can be verified that multiple hypersonic vehicles can achieve cooperative optimal formation in two combat scenarios through the effectiveness evaluation system and the PSACO algorithm according to simulation examples. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hypersonic vehicles

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