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International Conference on Guidance, Navigation and control, ICGNC 2024

作者： Zhu, Junfan Wang, Honglun Wang, Yanxiang Liu, Yiheng School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China The Science and Technology on Aircraft Control Laboratory Beihang University Beijing 100191 China Shenyuan Honors College Beihang University Beijing 100191 China Beijing Institute of Astronautical System Engineering Beijing 100076 China

ISBN: (纸本)9789819622115

The control of towed-cable-drogue system (TCDS) is important to achieving aerial recovery. In this paper, an adaptive prescribed performance control (APPC) based drogue controller is proposed to control drogue’s position while docking. First, the kinematic and dynamic models of controllable TCDS under multiple airflow disturbances are constructed. Second, the impact of command mutations and sudden disturbances may cause sudden increase of position tracking error and traditional PPC may encounter control singularity. To address the fragility of traditional PPC, an adaptive PPC is proposed. Combined with backstepping controller, the position controller is designed. Finally, the simulation results validate the effectiveness of the proposed method in addressing the control challenges of TCDS under command mutations and sudden disturbances. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Aerial recovery Prescribed performance control Towed-cable-drogue system

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Coverage control in Multiagent Games on Arbitrary Connected Networks

Coverage Control in Multiagent Games on Arbitrary Connected ...

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Asian control Conference

作者： Shaoqing Zhang Pengyang Fan Weiguo Xia Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology China Shenyang Aircraft Design and Research Institute Shenyang China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In this paper, we address the heterogeneous multiagent coverage control problem. While existing algorithms for coverage control are typically designed for specific communication network architectures, there is a notable gap between the available algorithms and the need for developing algorithms suitable for arbitrary connected communication networks. To mitigate this gap, we propose a distributed network adjustment strategy aimed at optimizing network structure to enhance the coverage performance across arbitrary connected communication networks. In terms of the coverage performance, we design a coverage utility function based on network games in dynamic networks and formulate a potential game function, thereby transforming the coverage game problem in dynamic networks into a max-min problem. Additionally, we introduce the Dynamic Network Region Coverage Algorithm to address the coverage game problem in dynamic networks. Finally, we validate the effectiveness of our algorithm through simulation experiments.

关键词： Network topology Heuristic algorithms Games Minimax techniques Numerical simulation Numerical models Communication networks

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A Novel Autonomous Collision Avoidance Decision Mechanism for UAV in Low Altitude Environment Based on 3D Dynamic Collision Region

A Novel Autonomous Collision Avoidance Decision Mechanism fo...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Zhang, Menghua Wang, Honglun Wu, Jianfa School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Shenyuan Honors College of Beihang University Beijing100191 China

ISBN: (纸本)9789811581540

Aiming at the autonomous collision avoidance problem for unmanned vehicles (UAVs) in low altitude environment, a novel decision mechanism based on 3D dynamic collision region is proposed in this paper. First, the models of collision avoidance are built, which relates to the UAV kinematic characteristics and the environment. Second, the 3D dynamic collision region is established, which contains the safety information of UAV relates to time and distance simultaneously. Besides, for the design of decision mechanism, the information given by the dynamic collision region is fully exploited and several novel definitions are proposed. Third, based on the safety criterions given by the dynamic collision region, a novel decision mechanism for collision avoidance is proposed. By choosing actions such as path re-planning and emergency maneuvers properly, the decision mechanism allows the UAV to better adapt to the complex environment and enhance the flight safety. Finally, simulations are carried out to verify the effectiveness of our proposed framework. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Dynamics

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Trajectory-Predicting Network: A Deep Learning Method Enhancing Feasibility of Path Planning

Trajectory-Predicting Network: A Deep Learning Method Enhanc...

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International Conference on Autonomous Unmanned Systems, ICAUS 2021

作者： Wen, Jiayun Wang, Honglun Liu, Yiheng School of Automation Science and Electrical Engineering Beihang University Beijing100191 China The Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Shenyuan Honors College of Beihang University Beijing100191 China

ISBN: (纸本)9789811694912

Feasibility of planned path represents the viability and accuracy for unmanned aerial vehicles (UAVs) to track. It is a bridge between UAV path planning and tracking, and also an important guarantee for the safe and efficient completion of the mission of UAV. At present, most researchers only take account of the simplified model and UAV state constraints when considering the path planning, but do not further consider the dynamics constraints of the UAV itself and the performance of the designed path tracking controller, which results in a certain distance error between the planned path and the actual trajectory. When UAVs perform missions in complex and dense areas, the actual trajectory generated by the planned path command even collides with obstacles, which is difficult to guarantee mission safety. This paper proposes a trajectory-predicting network (TPN) based on the deep learning, which characterize the complex nonlinear relation between the planning command and the actual trajectory considering nonlinear model and controller of the closed-loop system. In time of path planning, the predicted trajectory obtained by TPN corresponding to the planning command is evaluated to find the optimal planning command. The optimal trajectory is regarded as a planning path, and its corresponding command as path tracking control input of the control system. Simulation results verify the viability and effectiveness of the proposed method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Motion planning

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Deep Learning Based Bow Wave Modeling for UAV Aerial Refueling Docking

Deep Learning Based Bow Wave Modeling for UAV Aerial Refueli...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Lun, Yuebin Wang, Honglun Liu, Yiheng School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Shenyuan Honors College Beihang University Beijing100191 China

ISBN: (纸本)9789811581540

The autonomous aerial refueling (AAR) has become an effective way to prolong air combat time in modern warfare. However, the control of the docking process should be precise enough because of the strong instability of the drogue. The bow wave is an important factor in disturbing the motion of drogue which is few mentioned in relevant research. A deep learning method is proposed to estimate the effect of the bow wave, which is hard to be predicted by accurate modeling. Considering the authenticity of model, the computational fluid dynamics (CFD) analysis is used to obtain the experiment data in the docking. Through the simulations and comparison, it is proved that the model fitted by deep learning is more accurate and the calculation speed is faster, which provides a feasible way for online optimization of AAR. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computational fluid dynamics

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An Augmented Two-stage Robust Adaptive Filtering Algorithm Based on GMWM for PPP/SINS

An Augmented Two-stage Robust Adaptive Filtering Algorithm B...

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International Conference on Systems and Informatics (ICSAI)

作者： Luodi Zhao Zhao Long Digital Navigation Center Beihang University Beijing China Science and Technology on Aircraft Control Laboratory Beihang University Beijing China

In dynamic precise point positioning (PPP)/ strapdown inertial navigation system (SINS) integration, abnormal observations and system model errors are both of the most important factors affecting the positioning performance. Generally, adaptive robust filtering is used to lower the impact of abnormal observations and system model errors on navigation performance, which are difficult to be accurately identified and separated. Meanwhile, the navigation performance depends greatly on the filtering model which is closely related to the error model of the inertial sensors. The inertial stochastic error model is normally determined by experience which fail to reflect the real situation of the navigation system. An enhanced two-step robust adaptive filtering algorithm is proposed to address this issue. The algorithm can respectively identify and process the system model errors and the abnormal observations in two steps. Moreover, the stochastic error of inertial sensors is modeled by an art-of-state technique called the generalized method of wavelet moments (GMWM). The results of the practical car experiments indicate that the augmented algorithm can promote the positioning performance of PPP/SINS tightly-coupled system and enhance the robustness against the system model disturbance and abnormal observations.

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Distributed Cooperative control for Human-Unmanned Aerial Vehicle Swarm Teaming in Target Tracking*

Distributed Cooperative Control for Human-Unmanned Aerial Ve...

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IEEE International Conference on Robotics and Biomimetics

作者： Hangxuan He Mengzhen Huo Haibin Duan School of Automation Science and Electrical Engineering Beihang University Beijing PR China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing PR China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Over the last decade, the relationship between humans and cyber-physical systems has grown closer, particularly in fields such as manufacturing and transportation. This paper presents a control framework within the engineering domain, wherein a human operator collaborates with a swarm of unmanned aerial vehicles (UAVs) to achieve a shared goal. First, we construct a human-swarm mutual trust model that empowers both parties with a degree of autonomy. Second, we adopt a distributed optimization algorithm integrated with control barrier functions to manage the swarm's motion. The cooperative control framework is demonstrated in a 3D scenario, and simulation results verify the feasibility of the proposed method.

关键词： Three-dimensional displays Target tracking Simulation Transportation Collaboration Cyber-physical systems Autonomous aerial vehicles Manufacturing Optimization Robots

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3D Curved Path Tracking control for UAV Collision Avoidance in Low Altitude Environments

3D Curved Path Tracking Control for UAV Collision Avoidance ...

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International Conference on Autonomous Unmanned Systems, ICAUS 2021

作者： Zhang, Menghua Wang, Honglun Wu, Jianfa Xu, Pengya School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Institute of Control Engineering Beijing100190 China Shanghai Electro-Mechanical Institute Shanghai201109 China

ISBN: (纸本)9789811694912

Aiming at the 3D curved path tracking problem for fixed-wing unmanned vehicle (UAV) collision avoidance in low altitude environments, a path tracking control method is proposed based on the strategy of separated guidance-control design. First, considering the characteristics of six degree of freedom (6-DOF) motion equation of UAV including strong nonlinearity, tight coupling and nonaffinity, the affine transformation is performed on the UAV model for control design. Second, the path tracking control system is divided into the inner control loop and the outer guidance loop. Based on back-stepping linear active disturbance rejection control (BLADRC), the control loop is further divided into the angular rate loop, the angle loop and the ground speed loop, thus, corresponding controllers are designed respectively. For the design of guidance loop, acceleration commands of the UAV in vertical plane and horizontal plane are obtained by the L1 guidance algorithm, and corresponding angle commands are given by command transformation. Finally, the simulation results show that the UAV can track the desired path determined by the collision avoidance decision method accurately, thus the feasibility and the effectiveness of the proposed path tracking control method is verified. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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control and Implementation of 2-DOF Lower Limb Exoskeleton Experiment Platform

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Chinese Journal of Mechanical Engineering 2021年第1期34卷 3-19页

作者： Zhenlei Chen Qing Guo Huiyu Xiong Dan Jiang Yao Yan School of Aeronautics and Astronautics University of Electronic Science and Technology of ChinaSichuan 611731ChengduChina Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Sichuan 611731China Glasgow College University of Electronic Science and Technology of ChinaSichuan 611731China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaSichuan 611731China

In this study,a humanoid prototype of 2-DOF(degrees of freedom)lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and *** improve the detection accuracy of the humanrobot interaction torque,a BPNN(backpropagation neural networks)is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque ***,the backstepping controller is designed to realize the exoskeleton's passive position control,which means that the person passively adapts to the *** the other hand,a variable admittance controller is used to implement the exoskeleton's active followup control,which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable *** improve the wearable comfortable effect,serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control ***,the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.

关键词： Lower limb exoskeleton BP neural network Backstepping controller Variable admittance strategy

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Mixed Uncertainty Modelling And Analysis Of Rotor Dynamics For Power And Thermal Management System

Mixed Uncertainty Modelling And Analysis Of Rotor Dynamics F...

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2022 CSAA/IET International Conference on aircraft Utility Systems, AUS 2022

作者： Wang, Sen Li, Yang Shang, Yaoxing School of Automation Science and Electrical Engineering Beihang University Beijing China Ningbo Institute of Technology Beihang University Ningbo China Science and Technology on Aircraft Control Laboratory Beihang University Beijing China Research Institute for Frontier Science Beihang University Beijing China Ministry of Industry and Information Technology China

ISBN: (数字)9781839537769

ISBN: (纸本)9781839537769

The rotor-magnetic bearing system of the Power and Thermal Management System (PTMS) has a large length-to-diameter ratio and high rotational speed. The uncertainties introduced by machining and assembly errors and fluctuations in component characteristics are magnified on the rotor dynamics of the system. So it is necessary to research the dynamics of the system under the influence of those uncertainties. Based on the modelling of the PTMS shaft system, this paper studies the effect of probability-interval mixed uncertainty on rotor steady state response. The result shows that the uncertainties have a huge influence on the unbalanced responses of the rotor at critical speeds, and provides a reference model for the robust design of the magnetic bearing control. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Uncertainty analysis

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