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Highly constrained cooperative guidance for flexible landing on asteroids

Chinese Journal of Aeronautics 2025年第4期38卷 349-360页

作者： Chang LYU Zixuan LIANG Shengying ZHU School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration(Beijing Institute of Technology) Ministry of Industry and Information TechnologyBeijing 100081China

Flexible lander,composed of multiple nodes connected by flexible material,can reducethe bouncing and overturning during the asteroid *** satisfy the complex constraints inthe node cooperation of the flexible landing,an intelligent cooperative guidance method is *** method consists of a double-layer cooperative guidance structure,a guidance parameterdetermination approach,and an action priority *** double-layer contains a basic guid-ance used to satisfy the terminal state constraints,and a compensatory guidance used to satisfythe lander's attitude *** the compensatory guidance,the parameters are determinedby multi-agent system,which are trained according to the performance index of flexible landing *** action priority strategy is used to reduce the detrimental effect of parameter inconsis-tency on the node *** simulation of flexible landing shows that the cooperativeguidance method is effective in improving the landing accuracy while satisfying the ***,the method is robust to the disturbance in the navigation and control.

关键词： Asteroid Flexible lander Multi-constraint Cooperative guidance Reinforcement learning

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Data-driven output regulation control for constrained linear systems

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Science China(information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Fault diagnosis method of link control system for gravitational wave detection

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Journal of Systems Engineering and Electronics 2024年第4期35卷 922-931页

作者： GAO Ai XU Shengnan ZHAO Zichen SHANG Haibin XU Rui School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Ministry of Industry and Information TechnologyBeijing 100081China Key Laboratory of Dynamics and Control of Flight Vehicle Ministry of EducationBeijing 100081China

To maintain the stability of the inter-satellite link for gravitational wave detection,an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is *** from the traditional fault diagnosis optimization algorithms,the fault intelligent learning method pro-posed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong cou-pling *** constructing a two-layer learning network,the method enables efficient joint diagnosis of fault areas and fault *** simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s,and the fault diagnosis efficiency is improved by 99.8%compared with the traditional algorithm.

关键词： large scale multi-satellite formation gravitational wave detection laser link monitoring fault diagnosis deep learning

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Time-Varying Formation Tracking control of Heterogeneous Multi-Agent Systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems control theory autonomous systems Stability

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Optimal crater landmark selection based on optical navigation performance factors for planetary landing

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Chinese Journal of Aeronautics 2023年第3期36卷 254-270页

作者： Yi XIU Shengying ZHU Rui XU Maodeng LI School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Ministry of Industry and Information TechnologyBeijing 100081China Key Laboratory of Dynamics and Control of Flight Vehicle Ministry of EducationBeijing 100081China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control EngineeringBeijing 100091China

Planetary craters are natural navigation landmarks that widely exist and are easily *** navigation based on crater landmarks has become an important autonomous navigation method for planetary *** to the increase in observed crater landmarks and the limitation of onboard computation,the selection of good crater landmarks has gradually become a research hotspot in the field of landmark-based optical *** paper designs a fast crater landmark selection method,which not only considers the configuration observability of crater subsets but also focuses on the influence on navigation performance arising from the measurement uncertainty and the matching confidence of craters,which is different from other landmark selection *** factor of measurement uncertainty,which is anisotropic,correlated and nonidentically distributed,is quantified and integrated into selection based on crater pairing detection and localization error *** addition,the concept of the crater matching confidence factor is introduced,which reflects the possibility of 2D projection measurements corresponding to 3D *** with the configuration observability factor,the crater landmark selection indicator is ***,the effectiveness of the proposed method is verified by Monte Carlo simulations.

关键词： Crater-based optical navigation Crater landmark selection Crater matching Measurement uncertainty Planetary landing

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Laser-Link Acquisition Maneuver Planning for Gravitational Wave Detection under Coupled Multi-Axis Constraints

Laser-Link Acquisition Maneuver Planning for Gravitational W...

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2024 IAF Symposium on Ongoing and Near Future Space Astronomy and Solar-System Science Missions at the 75th International Astronautical Congress, IAC 2024

作者： Zhu, Zhe Xu, Rui Li, Zhaoyu Liang, Zixuan Long, Jiateng Zhu, Lei Institute of Deep Space Exploration Technology Beijing100081 China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Beijing Institute of Technology Ministry of Industry and Information Technology Beijing100081 China Shanghai Institute of Spaceflight Control Technology Shanghai201109 China

ISBN: (纸本)9798331312121

In space mission of gravitational wave detection carried out by formation flying satellites, the movable payloads of laser emitters and telescopes are built on each satellite to accomplish laser acquisition and accurate pointing. For three satellites that form an equilateral triangle configuration, for instance, each one requires scan and pointing of two laser beams emitted by two payloads respectively for intersatellite acquisition. Although movable payloads can provide additional degrees of freedom for attitude maneuver, the satellite maneuver paths are under restrictions of payload installation structure and slewing angle limit. With presence of sun-avoidance and other pointing constraints, the acquisition procedure involves the problem of attitude maneuver planning for satellite with movable payloads under pointing constraints applied to multiple body-fixed axes, i.e., coupled multi-axis constraints. On account of the problem that the feasible region of attitude maneuver under multi-axis constraints is limited, considering the slewing angle and configuration limit of payloads, the geometric projection diagram of payload pointing in two-dimensional state parameter space of azimuth and elevation is designed and forms a variable polygon. As each node of the polygon corresponds to a payload pointing, the polygon's deformation extent is confined by the coupled relationship of payloads and slewing range of them each. On the basis of the diagram, a dynamic constraint model is constructed. Furtherly, a path planning algorithm is raised by adopting synchronous transfer strategy to payload state nodes based on heuristic information. Considering the limitation of the payload polygon, deformation to extreme extent means using up the maneuverability of payloads, causing the attitude unwinding of satellite base. It's hoped that slewing angles of payloads are kept at an intermediate value. Based on this thought, in the process of path expansion of all polygon nodes, a heuristi

关键词： Motion planning

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Efficient optimization method for variable-specific-impulse low-thrust trajectories with shutdown constraint

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Science China(Technological Sciences) 2022年第3期65卷 581-594页

作者： JIA FeiDa QIAO Dong HAN HongWei LI XiangYu School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Ministry of Industry and Information TechnologyBeijing 100081China

This paper develops a sequential convex programming(SCP)-based method to solve the minimum-fuel variable-specific-impulse low-thrust transfer problem considering shutdown constraint,with emphasize on improving the computational *** variable parameter engine is more applicable for many low-thrust scenarios,therefore,both a continuously variable model and a ladder variable model are ***,the original problem is convexified by processing the constraint feasible domain,which is composed of the nonlinear dynamic equations and second-order equality constraint,into convex ***,the approximation is generated to close the optimal solution of the low-thrust problem by iteratively solving the convexified ***,the switching self-detection and adaptive node refinement methods are presented,which can improve the accuracy of the solution and accelerate the convergence during the approximation process and is especially necessary and effective in the scenarios with shutdown *** numerical simulations,the comparison with the homotopic approach shows that the proposed method only needs 4%computational time as that of the homotopic approach,and two variable-specificimpulse examples further demonstrate the effectiveness and efficiency of the proposed method.

关键词： low-thrust trajectory variable-specific-impulse shutdown constraint sequential convex programming switching self-detection and adaptive node refinement

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Scene image recognition with knowledge transfer for drone navigation

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Journal of Systems Engineering and Electronics 2023年第5期34卷 1309-1318页

作者： DU Hao WANG Wei WANG Xuerao ZUO Jingqiu WANG Yuanda School of Automation Southeast UniversityNanjing 210096China Autonomous Control Robot Laboratory Jiangsu Zhongke Institute of Applied Research on Intelligent Science and TechnologyChangzhou 213164China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and TechnologyNanjing 210044China

In this paper,we study scene image recognition with knowledge transfer for drone *** divide navigation scenes into three macro-classes,namely outdoor special scenes(OSSs),the space from indoors to outdoors or from outdoors to indoors transitional scenes(TSs),and ***,there are difficulties in how to recognize the TSs,to this end,we employ deep convolutional neural network(CNN)based on knowledge transfer,techniques for image augmentation,and fine tuning to solve the ***,there is still a novelty detection prob-lem in the classifier,and we use global navigation satellite sys-tems(GNSS)to solve it in the prediction *** results show our method,with a pre-trained model and fine tun-ing,can achieve 91.3196%top-1 accuracy on Scenes21 dataset,paving the way for drones to learn to understand the scenes around them autonomously.

关键词： scene recognition convolutional neural network knowledge transfer global navigation satellite systems(GNSS)-aided

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autonomous landing scene recognition based on transfer learning for drones

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Journal of Systems Engineering and Electronics 2023年第1期34卷 28-35页

作者： DU Hao WANG Wei WANG Xuerao WANG Yuanda School of Automation Southeast UniversityNanjing 210096China Autonomous Control Robot Laboratory Jiangsu Zhongke Institute of Applied Research on Intelligent Science and TechnologyChangzhou 213164China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and TechnologyNanjing 210044China

In this paper, we study autonomous landing scene recognition with knowledge transfer for drones. Considering the difficulties in aerial remote sensing, especially that some scenes are extremely similar, or the same scene has different representations in different altitudes, we employ a deep convolutional neural network(CNN) based on knowledge transfer and fine-tuning to solve the problem. Then, LandingScenes-7 dataset is established and divided into seven classes. Moreover, there is still a novelty detection problem in the classifier, and we address this by excluding other landing scenes using the approach of thresholding in the prediction stage. We employ the transfer learning method based on ResNeXt-50 backbone with the adaptive momentum(ADAM) optimization algorithm. We also compare ResNet-50 backbone and the momentum stochastic gradient descent(SGD) optimizer. Experiment results show that ResNeXt-50 based on the ADAM optimization algorithm has better performance. With a pre-trained model and fine-tuning, it can achieve 97.845 0% top-1 accuracy on the LandingScenes-7dataset, paving the way for drones to autonomously learn landing scenes.

关键词： landing scene recognition convolutional neural network(CNN) transfer learning remote sensing image

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Event-triggered-based self-organizing fuzzy neural network control for the municipal solid waste incineration process

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Science China(Technological Sciences) 2023年第4期66卷 1096-1109页

作者： HE HaiJun MENG Xi TANG Jian QIAO JunFei Faculty of Information Technology Beijing University of TechnologyBejing 100124China Beijing Laboratory of Smart Environmental Protection Beijing 100124China Beijing Key Laboratory of Computational Intelligence and Intelligent System Bejing 100124China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Bejing 100124China Xi'an Institute of Electromechanical Information Technology Xi'an 710065China

Due to the large uncertainty in the municipal solid waste incineration(MSWI)process,the furnace temperature of the MSWI process is difficult to control and the controller is updated *** improve the accuracy and reduce the number of controller updates,a novel event-triggered control method based correntropy self-organizing TS fuzzy neural network(ETCSTSFNN)is ***,the neurons of the rule layer are grown or pruned adaptively based on activation intensity and control error to meet the dynamic change of the actual operating ***,the performance index is designed based on the correntropy of tracking errors,and the parameters of the controller are adjusted by gradient descent ***,a fixed threshold event-triggered condition is designed to determine whether the current controller is updated or *** stability of the control system is proved based on the Lyapunov stability ***,the furnace temperature control experiments are conducted based on the actual data of a municipal solid waste incineration plant in *** experimental results show that the proposed ET-CSTSFNN controller shows a better control performance,which can reduce the number of the controller update significantly while achieving accurate furnace temperature control compared with other traditional control methods.

关键词： municipal solid waste incineration furnace temperature fuzzy control event-triggered

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