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Six-Degree-of-Freedom intelligent control of Hypersonic Flight Vehicle

IEEE Transactions on Aerospace and Electronic systems 2025年

作者： An, Hao Wang, Yiming Zhong, Xinyu Ye, Yongfeng Harbin Institute of Technology Space Control and Inertial Technology Research Center National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin China

The six-degree-of-freedom control of hypersonic flight vehicle (HFV) faces great challenges due to complex aerodynamics, inherent couplings and multiple constraints. This paper investigates the six-degree-of-freedom guidance and attitude control problem for unpowered gliding HFV. The guidance loop is based on the predictor-corrector method with three improvements of intelligent prediction acceleration, path constraints accommodation and no-fly zones circumvention. To quickly respond to guidance commands, three attitude channels (i.e., roll, pitch and yaw) are completely decoupled by nonlinear dynamic inverse, based on which a high-performance low-complexity attitude controller is proposed. This benefits from the appropriate integration of barrier function and sliding mode control, while design conditions of three alternative performances (i.e., asymptotic, exponential and preset-time convergences) are discussed. Servo dynamics and physical constraints of aerodynamic control surfaces are also well handled. © 2025 IEEE.

关键词： Hypersonic vehicles

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In-depth analysis of core-shell filaments in nonvolatile NbO_(x) memristive device as an artificial synapse for multifunctional bionic applications

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science China(Technological sciences) 2023年第12期66卷 3596-3603页

作者： JIANG Bei KE ShanWu TAO ZiPei JIN YaoYao MENG JiaHao SONG XingJuan XIAO YongYue JIANG Li WANG JinZhao CHEN Yong LI YueBin WEN Xin YE Cong School of Microelectronics Key Laboratory of Intelligent Sensing System and SecurityMinistry of EducationHubei UniversityWuhan 430062China Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and TechnologyWuhan 430074China School of Science Hubei University of TechnologyWuhan 430068China Faculty of Chemical Technology and Engineering West Pomeranian University of Technology in SzczecinSzczecin 71-065Poland

As a key building block of the biological cortex,synapses are powerful information processing units that enable highly complex nonlinear *** realization of artificial synapses with similar capabilities has important implications for building intelligent,neuromorphic ***,we demonstrate an artificial synapse based on NbO_(x) nonvolatile memristor to mimic multifunctional bionic applications such as nociceptor and associative *** experimental characterization with COMSOL simulation,the traditional resistance switching characteristics,which are the decisive factor for the synapse properties are in-depth *** can be proposed that the I-V characteristics of Pt/NbO_(x)/TiN memristor are governed by core-shell filaments consisting of the shell region of sub-stoichiometric Nb_(2)O_(5-δ)and the core of NbO_(2).On the basis of the core-shell filament model,it can be reasonably explained that Ohmic conduction and Poole-Frenkel conduction take turns to dominate the current flowing in the memristive device,leading to the zigzag evolution of current during the operation process of NbO_(x)-based *** simulations of synaptic plasticity,including long-term potentiation/depression(LTP/LTD),paired-pulse facilitation(PPF),and spike-timing-dependent plasticity(STDP),exhibiting that the NbO_(x) can be utilized for an artificial ***,bionic functions such as hyperalgesia and allodynia of a nociceptor and a series of associative learning behaviors in Pavlovian dog experiment are mimicked,illustrating that the Pt/NbO_(x)/TiN have great potential for highly simplified artificial neural network applications.

关键词： memristor core-shell filament synaptic plasticity nociceptor associative learning

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Facial expression recognition under occlusion conditions based on multi-feature cross-attention

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Journal of intelligent and Fuzzy systems 2024年第4期46卷 9841-9856页

作者： Guo, Sheng Tan, Mian Cai, Shan Zhang, Zaijun Liang, Yihui Feng, Hongxi Zou, Xue Wang, Lin School of Data Science and Information Engineering Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China School of Mathematics and Statistics Qiannan Normal University for Nationalities Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Duyun China Zhongshan Institute University of Electronic Science and Technology of China Zhongshan China Guizhou Aerospace Tianma Electromechanical Technology Co LTD Zunyi China

Although facial expression recognition (FER) has a wide range of applications, it may be difficult to achieve under local occlusion conditions which may result in the loss of valuable expression features. This issue has motivated the present study, as a part of which an effective multi-feature cross-attention network (MFCA-Net) is proposed. The MFCA-Net consists of a two-branch network comprising a multi-feature convolution module and a local cross-attention module. Thus, it enables decomposition of facial features into multiple sub-features by the multi-feature convolution module to reduce the impact of local occlusion on facial expression feature extraction. In the next step, the local cross-attention module distinguishes between occluded and unoccluded sub-features and focuses on the latter to facilitate FER. When the MFCA-Net performance is evaluated by applying it to three public large-scale datasets (RAF-DB, FERPlus, and AffectNet), the experimental results confirm its good robustness. Further validation is performed on a real FER dataset with local occlusion of the face. © 2024 – IOS Press.

关键词： Convolution

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The polarization filtering line spectrum extraction algorithm of underwater target signal

The polarization filtering line spectrum extraction algorith...

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2022 International Conference on Information Processing in Ocean science and technology, ICIPOST 2022

作者： Han, Xue Wang, Yang College of Intelligent System Science and Engineering Shenyang University Liaoning Shenyang110044 China Science and Technology on Underwater Test and Control Laboratory DaLian China

In order to increase the performance of underwater target line spectrum extraction, an adaptive polarization filtering line spectrum extraction method is researched in the paper. By using of the polarization characteristics of underwater target signals, the polarization characteristics of underwater target line spectrum signal is analyzed via singular value decomposition (SVD) method in frequency domain. Firstly, the line spectrum signal is presented by the eigenimage corresponding to the maximum singular value to increase the signal-to-noise ratio (SNR) of the signal. Then the polarization parameters are extracted according to the polarization characteristics of the line spectrum signals. And the line spectrum signal is filtered by constructing the polarization filtering function. The simulation results show that the output SNR of the proposed method are larger than that of conventional FFT analysis method when the SNR of the signal is larger than -9dB, and the detection probability of the proposed method is 100% when the SNR of the signal is -1 dB, while the detection probability of the conventional FFT analysis method is 27.73%. It shows that the proposed method provides a new approach for underwater line spectrum signal extraction techniques. © Published under licence by IOP Publishing Ltd.

关键词： Signal to noise ratio

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Graph-based Selection-Activation Reinforcement Learning for Heterogenous Multi-agent Collaboration 43

Graph-based Selection-Activation Reinforcement Learning for ...

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43rd Chinese control Conference, CCC 2024

作者： Chen, Hao-Xiang Zhang, Xi-Wen Shen, Jun-Nan Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System School of Automation Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401135 China

ISBN: (纸本)9789887581581

In practical applications of multi-agent systems, agents are often heterogeneous, and each type of them typically has different task objectives. For heterogeneous multi-agent reinforcement learning (HMARL), the diversity of agent types and the unbalanced agent number of each type can lead to the curse of dimensionality and non-stationary. Moreover, the increase in the number of heterogeneous agents may result in slow convergence during training. This paper proposes a graph-based selection-activation reinforcement learning (GSARL) method for training heterogenous multi-agent collaboration strategies. It first constructs agents based on their types, then extracts the global adjacency matrices and the ally adjacency matrices from the agents' observations, and calculates the global feature matrices. Afterwards, GSARL utilizes hierarchical graph convolutional network to sequentially convolve the global information and ally information, obtaining action logits based on agent types. By using the neural topology graph and the selection-activation method, the optimal multi-agent collaboration configuration is obtained through combinatorial optimization. Experiments are conducted in an adversarial combat simulation environment involving collaborative Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs). Simulation results show that the proposed method can accelerate convergence while allowing that each type of heterogeneous agents can leverage its unique advantages. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Unmanned aerial vehicles (UAV)

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Weak-Model Based Reinforcement Learning control Strategy of Aircraft Attitude system

Weak-Model Based Reinforcement Learning Control Strategy of ...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Huang, Dingcui Hu, Jiangping Peng, Zhinan Hao, Mingrui School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811581540

intelligent aircraft control is an important strategic development trend. Traditional aircraft control algorithms have a strong dependence on the system models, and it is difficult to cope with the increasingly complex battlefield environment for intelligent aircrafts. In this paper, an online intelligent controller design based on a weak-model reinforcement learning technology is proposed to solve stabilization problem of an aircraft. The control problem is firstly converted to an optimal control problem, then an adaptive dynamic programming (ADP) technology is applied for computing the corresponding nonlinear Hamilton-Jacobi-Bellman equation (HJB) equation. Then, actor-critic neural networks structures are established to learn the optimal controller online where only partial information of the aircraft dynamics is required. The proposed control strategy enables the aircraft to adjust and update its control strategy on-line according to the actual mission targets and environments, such that the requirements of autonomous learning and intelligent operation can be realized. Finally, simulation example is offered to validate the effectiveness of the proposed weak-model based controller design. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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Pattern Matching of Industrial Alarm Floods Using Word Embedding and Dynamic Time Warping

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 1096-1098页

作者： Wenkai Hu Xiangxiang Zhang Jiandong Wang Guang Yang Yuxin Cai School of Automation China University of GeosciencesWuhan 430074Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsWuhan 430074 Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China

Dear Editor,This letter proposes a new pattern matching method based on word embedding and dynamic time warping(DTW)to identify groups of similar alarm ***,alarm messages are transformed into numeric values that represent alarms and also reflect the relationships between alarm ***,similarities between numerically encoded alarm flood sequences are calculated by DTW and groups of similar floods are identified via *** effectiveness of the proposed method is demonstrated by a case study with alarm&event data obtained from a public industrial simulation model.

关键词： Word Alarm DTW

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Model and Simulation of Multipath Error in DLL for GPS Receiver

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Chinese Journal of Electronics 2025年第3期23卷 508-515页

作者： Lan Cheng Jie Chen Gang Xie Taiyuan University of Technology Taiyuan China Education Ministry Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

Although different multipath error models of Delay lock loop (DLL) used in GPS receiver are established, they have never been put together for comparison. Furthermore, no universal simulation method is developed to get a fair comparison among these models. A new model with implicate expression is hence proposed for the coherent DLL and the noncoherent Dot-product (DOT) power mode DLL. Meanwhile, a new simulation method based on the anonymous function in Matlab, which is especially suitable for models with implicit expression, is also proposed to compare the new model with the existing ones. The theoretical analysis and simulation results show that the existing models are the special case of the proposed one. The new simulation method can be used for the comparison of different multipath error models and the multipath error analysis of other DLLs for which only the implicit model is available.

关键词： Analytical models Tracking loops Codes Error analysis Simulation Receivers US Department of Transportation Mathematical models MATLAB Global Positioning system

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Research on Quadrature Suppression Method of Large Stiffness MEMS Disk Resonator Gyroscope Based on Axial Reconfiguration 16

Research on Quadrature Suppression Method of Large Stiffness...

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16th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2023

作者： Tang, Hao Zhou, Yi Zhou, Tong School of Mechanical Engineering Nanjing University of Science and Technology Nanjing China Jiangsu Research Center for Intelligent Navigation and Control of Complex Motion Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9798350327144

MEMS disk resonator gyroscope has become a hot research topic nowadays because of its excellent performance and processing advantages. This paper takes the large stiffness MEMS disk resonator gyroscope as the research object, and firstly establishes the dynamic equations in ideal and non-ideal states, studies the quadrature error mechanism of MEMS disk gyroscope, and analyzes the causes of serious quadrature coupling of large stiffness MEMS disk resonator gyroscope based on it;then a large stiffness MEMS disk resonator gyroscope quadrature suppression method based on axial reconfiguration is proposed for this problem. The method is based on the experimental calculation of the deflection angle of each stiffness axis of the gyroscope, pre-selection of the drive and sense axis with small quadrature coupling error, and the quadrature suppression of the large stiffness disk resonator gyroscope by means of electrostatic coupling stiffness correction;finally, the closed-loop control scheme of the large stiffness disk resonator gyroscope is proposed based on the method, including the closed-loop control of drive mode, quadrature error closed-loop suppression, and force rebalance detection control. Experiments show that the closed-loop control method based on axial reconstruction can effectively reduce the output bias of the gyroscope and improve the bias instability performance of the gyroscope, and its bias instability improves from 104.3°/h to 3.2°/h compared with the gyroscope under open-loop quadrature, open-loop detection, which verifies the effectiveness of the method on the performance improvement of large-stiffness MEMS disk resonator gyroscope. © 2023 IEEE.

关键词： Gyroscopes

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Novel Terminal Guidance Law for Blended Aero and Reaction-Jet Missile Based on Nonlinear Disturbance Observer 1

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Zhao, Hui Xu, Cheng Qin, Hehong Wang, Hao Hu, Ying Institute of Mechanical and Electrical Engineering Beijing100072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100072 China

ISBN: (数字)9789811694929

ISBN: (纸本)9789811694912

In this paper, an effective terminal guidance law is proposed for intercepting large maneuvering targets for the reaction jet control (RCS) missile. The guidance law takes the real dynamic characteristics of the control system into account, not only including the second order bandwidth filtering response of the autopilot, but also containing the discrete reaction jet force characteristics. For the target maneuver in the guidance loop, a new nonlinear disturbance observer (NDO) with fast convergence is presented on the premise of not obtaining the prior information of the target. Target acceleration and other uncertainties are estimated and compensated in the guidance law as a feed-forward input. Then the global stability of the system is proved by the appropriate Lyapunov function. The simulation results show that the guidance law can effectively intercept the maneuvering target and obtain good guidance precision. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Lyapunov functions

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