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11th IEEE Data Driven control and Learning Systems Conference, DDCLS 2022

作者： Lu, Xiaodong Wang, Chenzhao Huo, Junxin Wang, Wei School of Astronautics Northwestern Polytechnical University Xi'an710072 China National Key Laboratory of Science and Technology on Aircraft Control Facri Xi'an710065 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

As the fast mobility of position and uncertainty of quantity in the missiles swarm, the flooding routing protocol which is widely used in the communication of self-organized wireless network has unsatisfied communication capability and intolerable energy consumption under the large number of communication nodes with complex topology. To suppress these deficiencies, this paper studied a non-central multiagent routing protocol of self-organized network for missile swarm, which could provide random communication between multiple missiles in cooperative engagement. The proposed protocol regards each node as an agent with the capabilities of autonomous perception, independent decision-making and multihop communication. The agents receive the broadcast information with multihop lists from the neighbour nodes and build the connectivity matrix with the multihop depth. Considering the optimization function with communication load and energy consumption of each node, the agents update the forwarding routing table iteratively under the agents' connectivity matrix and right rotation rule. The mathematical simulation results showed that the proposed multiagent routing protocol could effectively reduce the network load and the energy consumption of each node than the flooding routing protocol. © 2022 IEEE.

关键词： Routing protocols

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Design and analysis of a novel hybrid cooling method of high-speed high-power permanent magnet assisted synchronous reluctance starter/generator in aviation applications

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Chinese Journal of Aeronautics 2023年第3期36卷 285-302页

作者： Hong GUO Xu HE Jinquan XU Wei TIAN Xiaofeng DING Laicai JU Dehong LI School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100083China Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing 100083China Ningbo Innovation Research Institute Ningbo 315800China School of Electrical and Information Engineering Jiangsu UniversityZhenjiang 212013China Beijing Shuguang Aviation Electric Co.LTD Beijing 101300China Aviation Industry Helicopter Design and Research Institute Jingdezhen 333001China

To improve the heat dissipation performance,this paper proposes a novel hybrid cooling method for high-speed high-power Permanent Magnet assisted Synchronous Reluctance Starter/Generator(PMa Syn R S/G)in aerospace *** hybrid cooling structure with oil circulation in the housing,oil spray at winding ends and rotor end surface is firstly proposed for the PMa Syn R S/*** the accurate loss calculation of the PMa Syn R S/G is proposed,which includes air gap friction loss under oil spray cooling,copper loss,stator and rotor core loss,permanent magnet eddy current loss and bearing *** parameter sensitivity analysis of the hybrid cooling structure is proposed,while the equivalent thermal network model of the PMa Syn R S/G is established considering the uneven spraying at the winding ***,the effectiveness of the proposed hybrid cooling method is demonstrated on a 40 k W/24000 r/min PMa Syn R S/G experimental platform.

关键词： Air gap friction loss Oil spray cooling Permanent magnet assisted synchronous reluctance starter/generator Thermal analysis Thermal network model

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Fault Modeling and Diagnosis for Spacecraft Attitude control System Using Deep Learning

Fault Modeling and Diagnosis for Spacecraft Attitude Control...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Guo, Pengyu Hu, Qinglei Wu, Huai-Ning Duan, Chao Chen, Bin Zhang, Peng School of Automation Science and Electrical Engineering Beihang University Beijing100190 China Beihang Hangzhou Innovation Institute Yuhang Hangzhou310023 China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing100190 China Peng Cheng Laboratory Shenzhen518000 China Beijing Institute of Control Engineering Beijing100094 China

ISBN: (纸本)9789811966125

The health monitoring system is significant for the reliable operation of spacecraft. In this paper, various fault models for controlling torque gyroscopes are established, and the learning network is trained with uniformly sampled data of fault. Then a data-driven fault diagnosis method based on deep learning is proposed. The method fully extracts the features to describe the classification of the multi-modal actuator faults, and trains the fault model with a large amount of spacecraft data under actuator faults. Then the rapid detection and classification of actuator faults are realized by the unknown fault model. Specifically, a spacecraft attitude control model is established to generate the sample data for the problem of insufficient fault data. Besides, the stack encoder is used to automatically reduce the data dimension and extract the main features from each set of data. Further, softmax classifier is introduced for fault model training. Finally, numerical simulations are illustrated to verify the reliability of the fault diagnosis method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Attitude control

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Spacecraft Integrated Pose Determination with Unknown Noise Covariances

Spacecraft Integrated Pose Determination with Unknown Noise ...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Chen, Hang Hu, Qinglei Wu, Huai-Ning Duan, Chao Chen, Bin Zhang, Peng School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beihang Hangzhou Innovation Institute Yuhang Hangzhou310023 China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Peng Cheng Laboratory Shenzhen518000 China Beijing Institute of Control Engineering Beijing100094 China

ISBN: (纸本)9789811966125

A novel robust unscented Kalman filter (UKF) is developed for orbiting spacecraft pose determination without knowing prior noise statistical characteristics by using dual quaternion formulation. First, an adjustment coefficient multiplied by a predesigned positive definite matrix is updated iteratively for the process noise covariance adaptation and the moving window of the measurement innovation are adopted for the measurement noise covariance estimation. Then, the adaptation method is incorporated into the dual-quaternion-based UKF procedure where the dual modified Rodrigues parameters (MRPs) are adopted for sigma points description to avoid violating the quaternion normalization constraint. Finally, the effectiveness and practical usefulness of the developed algorithm are verified via numerical simulation examples. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Covariance matrix

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Event-Triggered Distributed Multisensor Multitarget Tracking with GM-PHD Filter

Event-Triggered Distributed Multisensor Multitarget Tracking...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Qi, Jialin Zheng, Zhang Dong, Jin Hong, Jiang Xiwang, Dong Yu, Jianglong Zhang, Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China

ISBN: (纸本)9789811966125

This paper focuses on a distributed event-triggered Gaussian mixture probability hypothesis density (GM-PHD) filtering algorithm. In this algorithm, sensors transmit their Gaussian components to neighbors basing on the event-triggered conditions. Then Gaussian components are fused for certain times by matrix reformulation method. This algorithm can reduce data transmission and energy consumption with guaranteeing the estimation performance. Simulation experiment verifies the performance of this algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Matrix algebra

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MA-RRT∗ Algorithm for Path Planning with Maximum Rotation Angle Constraint and Adaptive Crossing Threat Zone 42

MA-RRT∗ Algorithm for Path Planning with Maximum Rotation A...

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42nd Chinese control Conference, CCC 2023

作者： Luo, Jiong Heng, Yong Li, Qi Hua, Yongzhao Dong, Xiwang Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Institute of Electronic System Engineering Beijing100854 China Institute of Artificial Intelligence Beihang University Beijing100191 China

ISBN: (纸本)9789887581543

With the gradual diversification of modern application scenes, the demand for UAV path planning is becoming more and more abundant. This paper first introduces a possible battle scenario, and the problems that must be considered in path planning in this scene are analyzed: the maximum rotation angle constraint and the demand that the UAV can cross the threat zone flexibly. Maximum rotation angle and Adaptive crossing threat zone RRT∗(MA-RRT∗) algorithm is proposed to solve the above problems. The algorithm improves the reconnection process of neighbor set in RRT∗, and adds the maximum rotation angle constraint to the RRT∗ framework, so that the generated path strictly meets this constraint. In addition, the above process also reduces the time consumption of RRT∗, and the speed advantage of MA-RRT∗ becomes more and more obvious with the increase of iteration times. Then, the obstacle information is regarded as one of the components of the node cost of the path, and the original obstacle is regarded as a soft constraint. This enables the path to adaptively cross the threat zone, which is more in line with the actual situation. We compare our algorithm with RRT∗ in numerical simulation, which verifies the effectiveness and time consumption advantages of the algorithm. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Motion planning

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UAV Path Planning from Human Demonstrations Using Inverse Reinforcement Learning

UAV Path Planning from Human Demonstrations Using Inverse R...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Xu, Zhiang Dong, Jin Hua, Yongzhao Dong, Xiwang Li, Qingdong Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China

ISBN: (纸本)9789811966125

In UAV path planning tasks, classical algorithms can only solve the tasks where environment is knowable and can be changed into mathematical model. For the tasks with unknown environment information is difficult to solve. However, such tasks can be easily solved by human. In this paper, we first bulid a UAV path planning environment and train the agent with deep reinforcement learning as human demonstration. Then, we use inverse reinforcement learning algorithm and processed human demonstrations to learn human policy. Finally, we test the trained policy in path planning tasks to verify the feasibility. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Dynamic Stiffness Analysis and Parameter Optimization of Digital Electro-Hydraulic Actuator 9

Dynamic Stiffness Analysis and Parameter Optimization of Dig...

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9th International Conference on Fluid Power and Mechatronics, FPM 2023

作者： Zhao, Tian-Yu Wu, Shuai Li, Wen-Ding Li, Ren-Jie Wang, Yi Song, Bing Fu, Jun-Yong Jiao, Zong-Xia School of Automation Science and Electrical Engineering Beihang University Beijing China Research Institute for Frontier Science Beihang University Beijing China Ningbo Institute of Technology Beihang University Ningbo China Shanghai Aerospace Control Technology Institute Shanghai China Shanghai Servo-system Engineering Research Center Shanghai China Beihang University Key Laboratory of Advanced Airborne Systems Beijing China Beihang University Science and Technology on Aircraft Control Laboratory Beijing China Tianmushan Laboratory Hangzhou China

ISBN: (数字)9798350304947

ISBN: (纸本)9798350304947

In this paper, the dynamic stiffness characteristics of digital electro-hydraulic actuator are analyzed, and the influence of the introduction of digital valve on the electro-hydraulic actuator is studied. Based on the actual working conditions and requirements of digital electro-hydraulic actuator, the dynamic stiffness models of digital electro-hydraulic actuator and servo valve controlled electro-hydraulic actuator are established respectively. Two testing methods were used to complete closed-loop dynamic stiffness simulation, and the digital valve control system and the servo valve control system are compared and analyzed. By changing different system parameters, the sensitivity analysis of dynamic stiffness parameters of digital electro-hydraulic actuator is realized. Finally, the optimization of system control parameters is realized, and the optimization direction of the system parameters of the digital electro-hydraulic actuator is provided. © 2023 IEEE.

关键词： Stiffness

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SOM Neural Network Based Gaussian Mixture PHD Algorithm for Multi-Sensor Multi-Target Tracking

SOM Neural Network Based Gaussian Mixture PHD Algorithm for ...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Zhang, Yujie Zheng, Hongwei Zhang, Zheng Yu, Jianglong Hua, Yongzhao Dong, Xiwang Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China

ISBN: (纸本)9789811966125

In the multi-sensor multi-target tracking (MSMTT) problem, the matching of the measurements and the targets will generate a huge computational burden, resulting in an unsatisfactory real-time performance of the maneuvering targets tracking. In order to reduce the computational burden, this paper proposes a self-organizing feature map (SOM) neural network based Gaussian mixture probability hypothesis density algorithm (SOM-GMPHD). Firstly, a distributed filtering MSMTT algorithm based on SOM neural network is proposed. The distributed SOM-GMPHD algorithm (DSOM-GMPHD) has two fusion steps. Secondly, to further reduce the computational complexity, a centralized SOM-GMPHD algorithm (CSOM-GMPHD) with only one-step fusion is proposed. The computational complexity analysis of the existing MSMTT algorithms (DGMPHD and CGMPHD) and the proposed SOM-GMPHD algorithms are carried out in this paper. Finally, the effect of the proposed algorithms is evaluated in the simulation experiment. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Self organizing maps

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Distributed Time-Varying Optimization for a Class of Second-Order Multi-agent Systems with Disturbance

Distributed Time-Varying Optimization for a Class of Seco...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Su, Piaoyi Zheng, Hongwei Yu, Jianglong Hua, Yongzhao Dong, Xiwang Ren, Zhang School of Automation Science and Electronic Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China Institute of Artificial Intelligence Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

This paper investigates the distributed convex time-varying optimization issue for multi-agent systems described by second-order with local disturbances produced by exosystems. Assuming each agent possessing a local cost function, the objective of this paper is to realize zero optimal tracking error considering the influences of extra disturbances and time-varying cost function simultaneously. Firstly, construst a local observer for each agent to obtain the accurate value of disturbance. Then, a distributed optimization algorithm is proposed to consensus optimal realization term. Thirdly, the system stability is confirmed by some Lyapunov-based analysis method. At last, in order to demonstrate the effectiveness of the proposed algorithm, a numerical simulation is constructed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cost functions

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