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Parameter Dynamic Selection Method of Multi-UAV Cooperative Search Based on Expert system

Parameter Dynamic Selection Method of Multi-UAV Cooperative ...

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Liu, Zhenchang Hao, Mingrui Wei, Donghui Liu, Yuting Zhao, Hongyin Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9789811966125

The cooperative search strategy is designed with the distributed model predictive method in this paper. For the rationality of decision-making of UAV swarm in different stages of the cooperative search, a dynamic parameter selection method based on the expert system is proposed. The weight of the objective function is adjusted online through the expert system so that the result of the search decision is more in line with the task requirements. Besides, a jump grid method is proposed for grid selection in cooperative search so that the UAV can select non-adjacent grids as the search point for the next time. The UAV's search frequency and trajectory maneuverability can be changed by adjusting the number of jump grids through the expert system. The simulation shows that the UAV with the expert system can dynamically adjust the search interval and search requirements, making the UAV swarm able to quickly discover targets, explore unknown areas, ensure collision avoidance, and meet the boundary constraints. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Rudder Health Monitoring and Data Visualization Based on Feature Extraction 10

Rudder Health Monitoring and Data Visualization Based on Fea...

引用

10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Zhou, Yajing Sun, Mingwei Hao, Mingrui Chen, Zengqiang College of Artificial Intelligence Nankai University Tianjin300350 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9781665424233

In order to monitor the health status of the rudder, this paper proposes a health monitoring method based on deep neural network through feature extraction. First, sufficient samples are obtained by data preprocessing. Then the feature dimension is reduced by using autoencoder, and the health monitoring can be carried out by combining with Softmax classifier. After proper tuning and comparison, proper network structure parameters can be obtained. Two kinds of images can be plotted by using the feature extraction of encoder to provide explicit contrast between the normal and abnormal rudders. The effectiveness of the proposed method can be demonstrated by numerical simulations. © 2021 IEEE.

关键词： Visualization

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Multi-Stage Marine Ship Recognition Based on Stackable Residual Network 19

Multi-Stage Marine Ship Recognition Based on Stackable Resid...

引用

19th International Conference on Natural Computation, Fuzzy systems and Knowledge Discovery, ICNC-FSKD 2023

作者： Yu, Wanwan Zhang, Junping Wang, Linlin Xi, Yunqiao Xu, Hongfeng Chen, Linxiu Hao, Mingrui Harbin Institute of Technology School of Electronics and Information Engineering Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350304398

Marine ship recognition has always been an important research field. The ships can be usually recognized by analyzing their attribute characteristics. However, in the actual process of recognition, many ship recognition methods using a single model cannot meet the requirements of this task due to the complexity of ship types, diversity of interference factors and different information obtained from distance differences. Therefore, we propose a multi-stage ship recognition scheme. First, the single radiation emitter feature recognition network model is designed for long-distance recognition. Second, the fusion feature network model for short distance recognition. The proposed network is mainly constructed with the residual units, which not only simplify the training of deep networks and facilitate the spread of information, but also can solve the vanishing gradient and exploding gradient problem. The simulation experimental results show that the proposed network model has better performance than typical methods and has great potential in applications. © 2023 IEEE.

关键词： Ships

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An infrared Radar fusion tracking algorithm based on adaptive fault tolerant filtering 40

An infrared Radar fusion tracking algorithm based on adaptiv...

引用

40th Chinese control Conference, CCC 2021

作者： Peng, Siting Lei, Li Ma, Yichao Youcheng, Wang Beijing Electro-Mechanical Engineering Institute Beijing100074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789881563804

In this paper, based on the fusion tracking of infrared and radar, a federated kalman filtering algorithm based on adaptive fault tolerance is designed. According to the observation equation of infrared and radar, a distributed fusion federated kalman filtering structure is established by using three infrared sensors and three radar sensors. The sub nodes filter their detection information respectively, and the estimation results are obtained. After that, the sub nodes filter results are sent into their part of fault-tolerant judgment respectively, then we can get the weight information of each sub node, thus it can determine the degree of dependence of each node, and the filtering results of all sub nodes are fused into calculation by their weight. The final simulation shows that the algorithm can isolate the interference in the multi-mode fusion tracking process effectively , and get a stable state estimation output. © 2021 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Tracking radar

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Zero-shot learning based on semantic embedding for ship detection 3

Zero-shot learning based on semantic embedding for ship dete...

引用

3rd International Conference on Unmanned systems, ICUS 2020

作者： Zhang, Zihan Zhoa, Jiajia Liang, Xinkai Northwestern Polytechnical University School of Electronics and Information Shaanxi Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing China

ISBN: (纸本)9781728180250

Zero-shot detection (ZSD) is a hot topic, which can detect unseen object without training on it. This new approach rises several challenges, e.g., the imbalance between positive and negative data, ambiguity between background and unseen classes, and how to align visual feature and semantic concept. In this paper, we apply an end-to-end zero-shot network to fulfil ZSD, where polarity loss is utilized to train detection model. polarity loss puts more importance on difficult data to reduce class imbalance and can maximize the difference between positive and negative predictions. Then, we use a semantic embedding method that use word vectors in both classification and regression subnets to better align visual features and semantic features. Finally, we use MS-COCO dataset as seen classes to train detection model, then we transfer the model for our own to detect warship object. Our model performs good on unseen classes and test accuracy of using polarity loss is apparently higher than that of using focal loss. © 2020 IEEE.

关键词： Zero-shot learning

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An Algorithm for Cooperative Navigation Using Neural Network to Identify Colored Noise Online

An Algorithm for Cooperative Navigation Using Neural Network...

引用

2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Sheng, Danting Cheng, Jin Li, Fengyi Hao, Mingrui Beijing Electro-mechanical Engineering Institute CASIC Beijing China HIWING Technology Academy of CASIC CASIC Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation CASIC Beijing China

ISBN: (纸本)9798350384185

In practical applications of cooperative navigation algorithms based on Kalman filtering, noise is often colored noise, which does not meet the requirement of Gaussian white noise for Kalman ***, an algorithm is proposed to identify and compensate for colored noise online using a BP neural ***, a cooperative navigation model based on Kalman filtering is ***, by studying the update process of Kalman filtering, the neural network is incorporated into the prediction calculation of the observations, following the online learning and updating of the Kalman *** simulations show that under conditions of colored noise, the results of the Kalman filter ***, after correction by the BP neural network, the filtering converges, providing high reference value for improving the accuracy of cooperative navigation. © 2024 IEEE.

关键词： Wiener filtering

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A Novel Attitude controller for Hypersonic Aircraft Based on FR-PI2

A Novel Attitude Controller for Hypersonic Aircraft Based on...

引用

International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Fan, Jiajun Li, Tianyi Guo, Xian Hao, Mingrui Sun, Mingwei College of Artificial Intelligence Nankai University Tianjin300350 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing100074 China

ISBN: (纸本)9789811581540

Due to the uncertainties and various noises of the Hypersonic Aircraft(HA), traditional method of designing attitude controllers based on accurate models faces immense challenges. To solve those proposed urgent problems effectively, in this paper, a innovative data-driven RL algorithm called FR-PI2 is proposed for the task of Hypersonic Aircraft attitude control, wherein several key techniques are introduced. Firstly, Hypersonic Aircraft attitude control is transformed into a stochastic optimal control problem, and the numerical solutions of the proposed stochastic optimal control problem are obtained with a path-integral-based method, called Policy Improvement with Path Integrals(PI2). Secondly, a model-free policy parameterization method with PID controller is integrated into the PI2 algorithm to ensure a low dependency of the Hypersonic Aircraft system model. Thirdly, a brand-new sample filtration method is proposed to guarantee rapid convergence, and an online optimization technology called rolling optimization is applied to guarantee optimality and real-time performance. Two series of experiments are carried out and analyzed to demonstrate the outstanding performance of the FR-PI2 algorithm. © 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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Radar Target Selection Strategy Based on Improved Subjective Bayesian Reasoning

Radar Target Selection Strategy Based on Improved Subjective...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Li, Wen Pei, Hucheng Qu, Guangzhou Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9789811694912

In order to deal with the influence of dilution passive decoy jamming on target selection of UAV radar, and to enable UAV radar have more independent decision-making ability to acquire the naval ship correctly in an ocean battlefield scene containing single real ship and multiple passive decoys, a method which established the mathematical simulation model of jamming scene, and used the model as the fitness function to calculate the adequacy measurement parameters of subjective Bayesian reasoning through genetic optimization algorithm is proposed. This method is applied to UAV radar target selection, compared with traditional target selection methods using single target feature, this method can improve the accuracy of ship acquisition by comprehensive using multi-dimensional target features. Moreover, this method can further improve the joint acquisition accuracy by setting multiple adequacy measurement parameters for different radars, which prove that the method can achieve the purpose of improving the success rate of UAV radar against dilution passive decoy jamming. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Radar

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Active Disturbance Rejection Gain Scheduling control of Hypersonic Vehicle Based on Guardian Maps 13

Active Disturbance Rejection Gain Scheduling Control of Hype...

引用

13th IEEE Data Driven control and Learning systems Conference, DDCLS 2024

作者： Zhang, Tingyu Wang, Yongshuai Sun, Mingwei Hao, Mingrui Chen, Zengqiang College of Artificial Intelligence Nankai University Tianjin300350 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9798350361674

This paper presented an adaptive gain scheduling algorithm for hypersonic vehicles with wide envelopes. First, the linear parameter variable parameter (LPV) model of hypersonic vehicles is established in the flight envelope. Then, the active disturbance rejection controller is considered to cope with disturbances and uncertainties, and the control gain is scheduled using the guardian maps method to adapt to the wide envelope of velocity and height. Finally, numerical simulation results show good control performance and meet the required performance indexes in all operating conditions, demonstrating the effectiveness and robustness of the proposed method. © 2024 IEEE.

关键词： Disturbance rejection

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Monocular Visual-Inertial Odometry Based on Point and Line Features 6

Monocular Visual-Inertial Odometry Based on Point and Line F...

引用

6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Chen, Gongyan Zhang, Hai Fu, Wenxing Qiao, Yiqun School of Automation Science and Electrical Engineering Beihang University Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728186351

In order to solve the problem that the point feature tracking is not robust enough to reduce the accuracy of the system in a low-texture environment, this paper proposes a visual inertial odometry system based on point-line features (PL-VINS). Firstly, the system improves the extraction and matching algorithm of line features to increase the speed and accuracy of the algorithm;then the line features are added to the front-end tracking and back-end optimization. Finally, the EuRoc public data set is used as the experimental object to prove the effectiveness of the algorithm. © 2020 IEEE.

关键词： Textures

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