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Overview of Research on Transformation of Multi-AUV Formations

complex system Modeling and Simulation 2021年第1期1卷 1-14页

作者： Bin Xin Junxi Zhang Jie Chen Qing Wang Yun Qu School of Automation and the State Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of TechnologyBeijing 100081China

Because of their wide detection range and rich functions,autonomous underwater vehicles(AUVs)are widely used for observing the marine environment,for exploring natural resources,for security and defense purposes,and in many other fields of *** with a single AUV,a multi-AUV formation can better perform various tasks and adapt to complex underwater *** changes in the mission or environment,a change in the UAV formation may also be *** the last decade,much progress has been made in the transformation of multi-AUV *** this paper,we aim to analyze the core concepts of multi-AUV formation transformation;summarize the effects of the AUV model,underwater environment,and communication between AUVs within formations on formation transformation;and elaborate on basic theories and implementation approaches for multi-AUV formation ***,this overview includes a bibliometric analysis of the related literature from multiple ***,some challenging issues and future research directions for multi-AUV formation transformation are highlighted.

关键词： autonomous underwater vehicle multi-AUV formation formation transformation formation control

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A maximum power point tracking controller for thermoelectric generators 36

A maximum power point tracking controller for thermoelectric...

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第36届中国控制会议

作者： Wei Xie Guangyue Huang Xiao Zhang Fang Deng School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems China ZhenHua Oil Co

ISBN: (纸本)9781538629185

Thermoelectric generators（TEGs） directly convert heat energy into electricity for power-supplying sensors and other portable electronic *** this paper,a maximum power point tracking（MPPT） controller in the modified perturb and observe（P＆O） algorithm was designed on the basis of analyzing the output characteristics of the TEG *** MPPT controller consists of a voltage sensor,a current sensor,a microcontroller and a SEPIC converter,which keeps the operating point of the thermoelectric generator tracking the maximum power point（MPP）.The thermoelectric generator was heated to generate electricity,and a supercapacitor accumulated that *** results using the MPPT controller present that the thermoelectric generator’s output voltage achieves around 5V,the output power achieves upward of 2W when the temperature difference △T=75℃,and the operating point of the thermoelectric generator accurately tracks the MPP with a tracking efficiency of 99.8%;the charging power can be improved 89.65%.

关键词： Thermoelectric generators（TEGs） Modified P＆O algorithm Maximum power point tracking（MPPT） SEPIC converter

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The Current Research Status of Unmanned Aerial Vehicle Maneuver Penetration decision-Making 5

The Current Research Status of Unmanned Aerial Vehicle Maneu...

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5th International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2024

作者： Zhuang, Yutao National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (纸本)9798331528911

In modern warfare, maneuver penetration is an essential aspect of unmanned aerial vehicle (UAV) combat operations. As the capabilities of both offensive and defensive sides continue to improve, the operational patterns of maneuver penetration scenarios are constantly evolving. This paper first introduces the maneuver capabilities and detection characteristics of both offensive and defensive systems in contemporary warfare, providing a macro definition of the maneuver penetration problem. Then, it conducts a survey and analysis of the applications of traditional and new artificial intelligence algorithms in maneuver penetration decision-making. Finally, it discusses the future research directions and challenges of artificial intelligence algorithms in this field and envisions the development of maneuver penetration decision-making. © 2024 IEEE.

关键词： Deep reinforcement learning

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Intersection Scan Model and Probability Inference for Vision Based Small-scale Urban Intersection Detection 28

Intersection Scan Model and Probability Inference for Vision...

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IEEE intelligent Vehicles Symposium

作者： Yang Yi Li Hao Zhu Hao Shang Songtian Lyu Ningyi Song Wenjie School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781509048052

Large-scale intersections stamped on maps have diverse visual features for detection, while small-scale urban intersections are hard to be identified especially when GPS signals are missing. In this paper, we propose a Hidden Markov Model (HMM) based small-scale intersection detection method utilizing monocular vision. We extract visual cues of road transformations and dynamic vehicles' tracks, and then design an Intersection Scan Model to obtain the potential traversable direction of the current road, which is the primary criterion of the intersection estimation. For better performances, we take the detections of consecutive frames into consideration and finally integrate them into HMM to estimate the probabilities of intersections. Results from KITTI datasets and real-world experiments have shown the functionality of the presented approach.

关键词： Hidden Markov models Roads Global Positioning system Vehicle dynamics Semantics Image segmentation Feature extraction

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Spatio-temporal decision-making and trajectory planning framework with flexible constraints in closed-loop dynamic traffic

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IET intelligent Transport systems 2023年第4期17卷 704-715页

作者： Zhang, Ting Fu, Mengyin Liu, Tong Song, Wenjie State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China Nanjing University of Science and Technology Nanjing China

Driving in interactive dynamic traffic is a huge challenge for autonomous vehicles, especially for motion planning. The autonomous vehicle not only needs to predict the future states of the social vehicles to avoid a collision but also realizes the comfort and continuous plan. To deal with the problem, a spatio-temporal decision-making and motion planning framework with flexible constraints based on previous work is proposed. Improvements can be highlighted in three aspects. First, a neural network for trajectory prediction is trained and it is integrated into the framework, which can learn the social vehicles' reactions in the negotiation better and give more accurate predictions. Second, instead of setting the fixed local targets, the flexible-constraint mechanism is introduced to increase the success rate of continuous planning, specifically, the local planning target is determined conditioned on the situation with an elastic factor. Third, two popular simulators with randomly disposed traffic participants are exploited, where vehicles are mutually influenced, more similar to real-world traffic. The closed-loop tests with zero crashes and the comparative experiments with traditional models demonstrate the superior performance and practical significance of the proposed framework. © 2022 The Authors. IET intelligent Transport systems published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Autonomous vehicles

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Pyramid histogram of oriented gradient and particles swarm optimization based SVM for vehicle detection

Pyramid histogram of oriented gradient and particles swarm o...

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2013 7th International Conference on Image and Graphics, ICIG 2013

作者： Wang, Hailuo Bo, Wang Sun, Li College of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

ISBN: (纸本)9780769550503

Vehicle Detection is an important part in intelligent transportation system (ITS) and driver assistance system. Considering vehicles have strong edges and lines in different orientation and scales, in this paper, we presents a method for detecting vehicles based on a feature named Pyramid Histogram of Oriented Gradient. This feature provides spatial distribution information of edges which was often ignored by other features. Specifically, we extract PHOG features from a traffic image and a vector is obtained as representation of this image. In order to speed up the process of calculation, Principle Component Analysis (PCA) algorithm is applied to these vectors to reduce their dimensionality. Tests show the efficiency improved significantly. Theses representative vectors are then used to train SVM classifier. To ensure the final classification accuracy, we adopt Particles Swarm Optimization (PSO) method to gain the parameters used in SVM classification. Optimal parameters correspond with optimal result. Experiments demonstrate the superiority of the proposed approach which has achieved an average accuracy of 95% on test images. © 2013 IEEE.

关键词： Vehicles

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Circadian Rhythms Recovery Based on Slide Mode controller 34

Circadian Rhythms Recovery Based on Slide Mode Controller

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第三十四届中国控制会议

作者： ZHOU Ren REN Haipeng HUANG Xiaona Department of Information and Control Engineering Xi'an University of Technology Shaanxi Key Laboratory for Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781467374439

Disrupting the circadian rhythms will cause health problems such as sleep disorders, memory disorders and obesity. Finding the suitable external stimulation to synchronize a model with a desired phase is a biologically significant issue. The phase control of circadian rhythms for Drosophila is considered from control engineering viewpoint in this paper. If all parameters of the model are known, we can use the feedback linearization to design a tracking controller for the phase ***, in practice, parameters uncertainties always exist. To deal with this problem, a slide-mode controller is proposed for the phase tracking control of circadian rhythms. The simulation results show the effectiveness of the proposed method.

关键词： Circadian rhythms,Circadian phase,Parameter uncertainty,Slide mode control

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Target Assignment Optimization of Heterogeneous Sensor Networks in Urban Environment 39

Target Assignment Optimization of Heterogeneous Sensor Netwo...

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39th Chinese control Conference, CCC 2020

作者： Chen, Chen Zihao, Cheng Wei, Xu Beijing Institute of Technology School of Automation Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing100081 China

ISBN: (纸本)9789881563903

Preventing and controlling Low-Slow-Small(LSS) targets are problems to be solved due to their good concealment in urban environment. Consequently, the problem of target assignment is studied in this paper. Firstly, a target assignment model based on heterogeneous sensor networks is proposed. The characteristics of LSS targets and the influence of environmental factors such as climate and terrain are considered on this model. At the same time, the detection capabilities of different detection nodes and collaborative tracking capabilities are also considered. Secondly, an intelligent optimization algorithm GSAPSO based on PSO is proposed to maximize tracking effect of the sensors. Finally, the simulations are used to compare the GSAPSO algorithm with the traditional PSO and GAPSO algorithms. The results demonstrate that the proposed algorithm has better tracking effect. © 2020 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Particle swarm optimization (PSO)

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Sensor Fault Detection with Online Sparse Least Squares Support Vector Machine

Sensor Fault Detection with Online Sparse Least Squares Supp...

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第三十二届中国控制会议

作者： Guo Su Deng Fang Sun Jian Li Fengmei School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex

ISBN: (纸本)9781479900305

In this paper,we present the theory of online sparse least squares support vector machine(OS-LSSVM) for prediction and propose a predictor with OS-LSSVM to detect sensor *** principle of the predictor and its online algorithm are *** with the traditional least squares support vector machine(LSSVM),OS-LSSVM has an advantage on training speed owing to the online training algorithm based on the base vector *** real-time output data of sensor is employed as the training vector to establish the regression *** method is compared with the LSSVM predictor in the *** typical faults of sensors are investigated and the simulation result indicates that the OS-LSSVM predictor can diagnose sensor fault accurately and rapidly,thus it is especially suitable for online sensor fault detection.

关键词： sensor fault detection OS-LSSVM LSSVM

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An overview of recent progress in high-order nonholonomic chained system control and distributed coordination

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Journal of control and decision 2015年第1期2卷 64-85页

作者： Jie Huang Jie Chen Hao Fang Lihua Dou School of Automation Beijing Institute of TechnologyBeijingChina State Key Laboratory of Intelligent Control and Decision of Complex Systems BeijingChina Fujian Institute of Education FuzhouChina

This paper reviews some main results and progress concerning with nonholonomic system control,especially focusing on the networked chained system *** controllability of nonholonomic system,the control method of nonholonomic system,the chained form transformation,the basic graph theory for multi-agent systems are recalled,*** important definitions,lemmas,theorems and dynamics are *** the consensus and formation control problems for networked nonholonomic chained systems are ***,some open questions are proposed.

关键词： distributed coordination multi-agent system nonholonomic system chained system high-order

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