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Parameter-Free Shifted Laplacian Reconstruction for Multiple Kernel Clustering

IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1072-1074页

作者： Xi Wu Zhenwen Ren F.Richard Yu the School of National Defence Science and Technology Southwest University of Science and TechnologyMianyang 621010China the School of National Defence Science and Technology Southwest University of Science and TechnologyMianyang 621010 the Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou UniversityWuzhou 543002 the Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen 518060China

Dear Editor,This letter proposes a parameter-free multiple kernel clustering(MKC)method by using shifted Laplacian *** MKC can effectively cluster nonlinear data,but it faces two main challenges:1)As an unsupervised method,it is up against parameter problems which makes the parameters intractable to tune and is unfeasible in real-life applications;2)Only considers the clustering information,but ignores the interference of noise within Laplacian.

关键词： parameter letter Parameter

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Mars Terrain Segmentation Algorithm Based on Improved PSPNet

Mars Terrain Segmentation Algorithm Based on Improved PSPNet

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2023 International Conference on Optics and Machine Vision, ICOMV 2023

作者： Zhou, Peng Xiong, Kai Beijing Institute of Control Engineering Beijing100090 China Science and Technology on Space Intelligent Control Laboratory Beijing100094 China

ISBN: (纸本)9781510664777

Planet rovers are becoming more and more crucial as deep space exploration missions develop. Accurate terrain segmentation can increase the rovers' capacity for independent detection. At present, the task of Mars terrain segmentation is difficult and the computational resources on rover are limited. This paper proposes an improved PSPNet algorithm for Mars terrain segmentation. MobileNetV2 is a lightweight network that replaces ResNet as the feature extraction backbone network. The channel attention mechanism SEnet is integrated into the network structure to improve the network's feature extraction capability. The experimental results show that the number of parameters and calculation amount of M-PSPNet are greatly reduced when compared to traditional PSPNet, but the recall rate of M-PSPNet on soil, bedrock, sand, and big rock can reach 92%, 91%, 86%, and 72%, respectively. Engineering-wise, the M-PSPNet is competitive. © 2023 SPIE. All rights reserved.

关键词： Rovers

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The Design and Implementation of Magnetic control of Ultra Quiet control System in Gravity Satellite 10th

The Design and Implementation of Magnetic Control of Ultra Q...

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10th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2022

作者： Guan, Bin Liu, Yiwu Liu, Qirui Li, Yan Fan, Jiakun Beijing Institute of Control Engineering Beijing100190 China Science and Technology on Space Intelligent Control Laboratory Beijing100190 China

ISBN: (纸本)9789811999673

In order to obtain gravity field data with high-precision, ultra quiet control should be applied in the attitude control system to reduce the influence of micro vibration caused by attitude control, since the measurement accuracy of the high-precision acceleration of the key load of the gravity measurement satellite has reached the level of 10 - 10m / s 2. A set of ultra quiet control system of magnetic control with high-precision is proposed in the paper, which makes the magnetic control accuracy reach the high-precision level of 0.01mNm and establishes an "extremely quiet" working environment for high-precision acceleration load by improving the geomagnetic field acquisition accuracy and high-precision magnetic torquer control. According to the data analysis of orbit, the result shows that the micro vibration environment of the magnetic control system has reached the ug level. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： control systems

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Angles-Only Onboard Initial Relative Orbit Determination with Auxiliary Satellite 8th

Angles-Only Onboard Initial Relative Orbit Determination wit...

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8th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2021

作者： Li, Jiaxing Yuan, Li Zhang, Cong Zhang, Sihang Beijing Institute of Control Engineering Beijing100190 China Science and Technology on Space Intelligent Control Laboratory Beijing100190 China

ISBN: (纸本)9789811933868

Onboard initial relative orbit determination (IROD) by using angle measurements is the key to space Situational Awareness. The camera offset measurement method is one of the most used IROD methods when only the angle measurement is available, which can overcome the range-observability problem caused by signal-camera measurement. However, the camera offset method cannot estimate the relative-position/-velocity when the chaser-target distance is much larger than the camera offset value, which is often below five meters. To overcome this problem, an auxiliary satellite treated as the chaser’s camera with known offset is proposed in this paper, which is suitable for satellites without cameras, and the IROD algorithm is also conducted correspondingly. The Tschauner–Hempel relative orbital motion dynamics and measurement model are given first. Then the IROD algorithm is yielded as a compact form by using the state augmentation least square method. Finally, a two-body satellite’s orbit dynamics model is built to generate simulation data, and three scenarios are studied to verify the convergence of the proposed IROD algorithm. Simulation results validate the proposed IROD algorithm converges quickly, and the measurement time corresponding to the lowest relative-position estimation error is related to the distance among the target, the chaser and the auxiliary satellite. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Satellites

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An Estimation Algorithm of Population Feature Distribution for the Imaging Constellation Task Planning Problem 42

An Estimation Algorithm of Population Feature Distribution f...

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42nd Chinese control Conference, CCC 2023

作者： Ding, Yinan Lei, Yongjun Wang, Shuyi Beijing Institute of Control Engineering Beijing100094 China Science and Technology on Space Intelligent Control Laboratory Beijing100094 China

ISBN: (纸本)9789887581543

An estimation algorithm of population feature distribution (EPFD) is proposed to improve the completion and imaging quality of imaging constellation observation tasks. Firstly, the observation task constraints and on-board resource constraints of agile imaging satellites are analyzed, the objective function of evaluating task completion and imaging quality is constructed, and the task planning model of agile imaging constellation is established. Then, the coding and decoding strategy with imaging time as the optimization object is designed. The concepts of global heuristic information and local heuristic information are given. A method for establishing the probability distribution model of imaging time based on heuristic information and a population evolution method are proposed. The directional search of imaging time is realized, and the completion of observation tasks and imaging quality are improved. Finally, the algorithm and particle swarm optimization algorithm are compared and analyzed through engineering examples. The results show that the algorithm has a fast convergence speed and a good optimization effect. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Particle swarm optimization (PSO)

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Liquid-filled spacecraft finite-time attitude maneuver control with attitude and angular velocity constraints 74

Liquid-filled spacecraft finite-time attitude maneuver contr...

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74th International Astronautical Congress, IAC 2023

作者： Guo, Yanning Zhang, Wei Ma, Guangfu Lyu, Yueyong Zhang, Haibo Harbin Institute of Technology China Beijing Institute of Control Engineering China National Key Laboratory of Science and Technology on Space Intelligent Control China

With development of aerospace industry, the mass of liquid fuel carried by spacecraft is also increasing in order to complete more complex space exploration missions, such as on-orbit refueling and space debris removal. And there is large liquid fuel consumption when spacecraft completes attitude and orbit maneuver, which greatly increases the nonlinearity and uncertainty of spacecraft dynamics and brings great challenges to spacecraft attitude maneuver control. Considering that during attitude maneuver, the control torque is easy to stimulate the liquid slosh, which will affect the attitude control performance and even lead to instability of the system. So it is necessary to constrain the angular velocity during attitude maneuver. In this paper, we consider the large angle attitude maneuver control of liquid-filled spacecraft system. Because of the consumption of liquid fuel, then the mass property of system is unknown and slowly time varying. So a novel finite-time attitude maneuver control law based on barrier Lyapunov function (BLF) and backstepping method in the presence of unknown, time varying system dynamics and angular velocity constraint, which aims at avoidance of violent liquid slosh, is proposed in this paper. Firstly, the sloshing liquid in a partially filled tank carried by the spacecraft is equivalent to a sloshing slug - a sphere of uniform density with a variable radius, and the rigid-liquid coupling dynamic equations with unknown parameters of the spacecraft are deduced by using the law of conservation of moment of momentum. Secondly, a finite-time prescribed performance function (FTPPF) is proposed to guarantee the convergence of spacecraft attitude error to zero within the setting time, with the help of FTPPF and the angular velocity constraint, a time-varying BLF and a logarithmic BLF are proposed correspondingly. Furthermore, a backstepping control law is designed for the spacecraft attitude maneuver based on augmented Lyapunov functions, mean

关键词： Angular velocity constraint Attitude constraint Backstepping control Backstepping control Liquid-filled spacecraft

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A Memristive Spiking Neural Network Circuit for Bio-Inspired Navigation Based on Spatial Cognitive Mechanisms

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IEEE Transactions on Biomedical Circuits and Systems 2025年第3期19卷 686-698页

作者： Chen, Zhanfei Wang, Xiaoping Wang, Zilu Yang, Chao Huang, Tingwen Lai, Jingang Zeng, Zhigang School of Mechanical Engineering and Automation Shenzhen518055 China Huazhong University of Science and Technology The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Hubei Key Laboratory of Brain-Inspired Intelligent Systems School of Artificial Intelligence and Automation Wuhan430074 China Guangxi University of Science and Technology School of Computer Science and Technology Liuzhou545006 China Shenzhen University of Advanced Technology School of Computer Science and Control Engineering Shenzhen518055 China

Cognitive navigation, a high-level and crucial function for organisms' survival in nature, enables autonomous exploration and navigation within the environment. However, most existing works for bio-inspired navigation are implemented with non-neuromorphic computing. This work proposes a bio-inspired memristive spiking neural network (SNN) circuit for goal-oriented navigation, capable of online decision-making through reward-based learning. The circuit comprises three primary modules. The place cell module encodes the agent's spatial position in real-time through Poisson spiking;the action cell module determines the direction of subsequent movement;and the reward-based learning module provides a bio-inspired learning method adaptive to delayed and sparse rewards. To facilitate practical application, the entire SNN is quantized and deployed on a real memristive hardware platform, achieving about a 21 × reduction in energy consumption compared to a typical digital acceleration system in the forward computing phase. This work offers an implementation idea of neuromorphic solution for robotic navigation application in low-power scenarios. © 2007-2012 IEEE.

关键词： intelligent robots

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One-step Framework for RF-Based Drone Identification 5

One-step Framework for RF-Based Drone Identification

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5th International Conference on Computer Vision, Image and Deep Learning, CVIDL 2024

作者： Ge, Jiaxin Zhang, Hanshuo Li, Jinhui Wen, Zhijin Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing China Xidian University Xian China

ISBN: (纸本)9798350373820

With the popularity of drones, incidents that threaten public safety caused by drones occur more frequently. In drone control and countermeasures scenarios, it is needed to further identify drones of the same type based on type recognition in order to determine the specific source of the signal. Existing schemes are multistep, which increases the complexity and overhead of post-maintenance. In this work, we propose a joint scheme based on RE fingerprinting where the type and individual belonging to the same type are identified in one step. Specifically, we adopt short-time Fourier transform to calculate the spectrogram of the received signal and label the types and individuals of the drone signals on the spectrogram to develop a data set. Based on the data set, we train a YOLOv5 neural network to extract detailed RF characteristics to identify which type and individual the signal belongs to. To further improve the identification performance, we introduce grayscale image colorization. Furthermore, we use median filtering to reduce noise and protect image edge information. Results on data set composed of real signals from 18 drones of 9 types show the classification accuracy of our proposed framework reaches over 98% at saturation and 3% higher than the method without grayscale image colorization. © 2024 IEEE.

关键词： Drones

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Asteroid Image Inpainting Method Based on Accelerated Diffusion Model 9

Asteroid Image Inpainting Method Based on Accelerated Diffus...

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9th International Conference on intelligent Computing and Signal Processing, ICSP 2024

作者： Zheng, Yunyun Huang, Xiangyu Beijing Institute of Control Engineering Science and Technology Space Intelligence Control Laboratory Beijing China

ISBN: (纸本)9798350376548

To mitigate the threat of asteroid impact on life on Earth, non-nuclear kinetic energy high-speed impact has been identified as the most viable strategy. To ensure accurate impact on the asteroid's center of mass with maximum kinetic energy, high-precision and high-speed autonomous optical navigation is necessary during the probe's approach to the asteroid. Autonomous optical navigation is crucial due to the difficulty of using historical tracking data such as astrometry on the ground, given the long distance between the asteroid and the probe. The navigation image is used to extract the centroid of the target asteroid, with the center of gravity of the asteroid profile serving as the impact point to provide a stable impact direction. It is important to note that asteroids have irregular shapes, fast spin, and rapidly changing bright regions. The shadow area of the asteroid is constantly changing due to illumination, which causes bias in the impact point due to the incomplete profile. To complete the contour of the target asteroid, a method based on the accelerated diffusion model (ADM) is proposed to inpainting the shadow area. ADM is fast enough for mission and has been found to have the highest accuracy index and the lowest centroid deviation after restoration when compared to several advanced image restoration methods. © 2024 IEEE.

关键词： Restoration

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Multi-Satellite Mission Planning Method for Dynamic Targets Based on Reinforcement Learning

Multi-Satellite Mission Planning Method for Dynamic Targets ...

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2023 China Automation Congress, CAC 2023

作者： Liu, Yilong Zhang, Cong Zhang, Sihang Li, Jiaxing Beijing Institute of Control Engineering Beijing China Beijing Institute of Control Engineering Science and Technology on Space Intelligent Control Laboratory Beijing China

ISBN: (纸本)9798350303759

The autonomous mission planning problem of space targets tracking with multi-satellite is studied in this paper. For effective evaluation of different candidate tracking resource combinations, a tracking performance evaluation model based on GDOP is proposed firstly, then a tracking priorities evaluation model for maneuverable dynamic targets is designed to autonomous evaluate and update the planning priorities during the tracking. To solve the problem of conflict resolution of tracking resources scheduling, the reinforcement learning algorithm is applied, considering of restricted computation resources onboard. A pointer network is utilized as the strategy model, with the tracking targets and corresponding priorities, the tracking performance evaluation of each potential candidate tracking resources combinations as input tensors, and the tracking tasks allocation of multi-satellites will be inferenced by the network accordingly. The actor-critic reinforcement learning algorithm is selected for training. It is shown that the algorithm proposed can formulate better planning strategies than the heuristic method, which reduces the mean tracking error by 21% during the whole tracking process. © 2023 IEEE.

关键词： Reinforcement learning

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