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31st European Safety and Reliability Conference, ESREL 2021

作者： Qiao, Yajing Shi, Jian Wang, Shaoping Liu, Weiqi School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Ningbo Institute of Technology Beihang University Ningbo315800 China

ISBN: (纸本)9789811820168

In order to optimize the layout of sensor measuring points for accurate fault location, this paper establishes the power transfer model from the view of power flow existing in the complex electromechanical system and studies the power-transfer based fault state propagation process. Taking aircraft actuation system as an illustration, this paper analyzes the power flow transferring process from permanent magnet DC motor to piston pump and hydraulic cylinder. Based on the power transfer model, the fault state propagation process is then established and analysed. The detectable condition and the attenuation law of fault detection sensitivity are found by the first-order trajectory sensitivity theory. The results indicate that as the distance between the measuring point of the sensor and the fault location becomes farther, the fault detection sensitivity attenuates. Therefore, it should be detected as close as possible to the fault location. The proposed method in this paper can describe the fault state propagation process of the system and verify the validity and accuracy of the theoretical analysis, which provide the basis for fault location and diagnosis based on power flow. © ESREL 2021. Published by Research Publishing, Singapore.

关键词： Energy dissipation

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Robust Bipartite Output Consensus Tracking for Heterogeneous Multi-agent Systems via Output Regulation Method

Robust Bipartite Output Consensus Tracking for Heterogeneous...

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Chinese control and Decision Conference, CCDC

作者： Chenglin Han Mengji Shi Tong Li Weihao Li Boxian Lin Kaiyu Qin School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu China The Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu China AVIC Chengdu Aircraft Design and Research Institute Chengdu China

This paper focuses on the robust bipartite output consensus tracking problem of heterogeneous multi-agent systems with model uncertainties. Firstly, the linearly parameterized neural networks are adopted to approximate the uncertain parts of the system model. Then, the adaptive update laws are constructed for the unknown parameters. Based on the output regulation method, the robust adaptive state feedback bipartite consensus tracking controller is proposed for the follower agents. In addition, according to the Lyapunov stability theorem, we have proved that the bipartite output consensus tracking control of multi-agent systems is achieved. Finally, some numerical simulation results are given to verify the effectiveness of the proposed control scheme.

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Preshaping Trajectory Optimization and control of Flexible Hypersonic Vehicle for Vibration Suppression

Preshaping Trajectory Optimization and Control of Flexible H...

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Chinese control Conference (CCC)

作者： Yifang Tang Chaofang Hu Yongtai Hu School of Electrical and Information Tianjin University Tianjin P.R. China Aviation Key Laboratory of Science and Technology on Aircraft Control Facri Xi'an P.R. China

Considering the special structural design and complex working conditions of flexible hypersonic vehicles, elastic vibrations can tremendously affect the control performance of hypersonic vehicles. In this paper, from the perspective of trajectory, a vibration suppression strategy for hypersonic vehicle including trajectory optimization and input shaping is proposed. The minimum sum of the squares of elastic modes and derivatives is selected as the performance index, and the optimal trajectory is calculated through direct collocation method. Then, an input shaper is designed for the first-order elastic mode to reshape the optimal trajectory. Meanwhile, the Tube model predictive control (Tube-MPC) is utilized to ensure the stable flight of the vehicle. Finally, the simulation results demonstrate the effectiveness of the proposed method.

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A Novel Method for aircraft Actuator Fault Diagnosis Based on Causal Graph and T-S Fuzzy Model

A Novel Method for Aircraft Actuator Fault Diagnosis Based o...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Chen, Yu Tao, Laifa Li, Yue Wang, Qiang Suo, Mingliang Zhao, Zhengduo Institute of Reliability Engineering Beihang University Beijing100191 China Science and Technology Laboratory on Reliability and Engineering Beihang University Beijing100191 China School of Reliability and Systems Engineering Beihang University Beijing100191 China Beijing Aerospace Automatic Control Research Institute Beijing100854 China Shenyang Aircraft Design and Research Institute Shenyang City110000 China

ISBN: (纸本)9789811966125

Proper assessment of the health status of the flight control system actuators, a critical system of the aircraft, is a prerequisite for proper aircraft operation. Timely and accurately determining the status of aircraft actuators help reduce the impact of faults. Obtaining knowledge related to fault information from actuator operation data and applying fault knowledge for diagnostic decisions is a crucial step in determining actuator status. In this paper, a novel fault diagnosis method is proposed by combining the causal inference method with the T-S fuzzy model. The proposed method improves the diagnostic decision performance of actuator faults by improving the fault knowledge acquisition process. The causal inference approach helps to obtain causal graph expressing the relationship between aircraft actuator parameters and states from actuator operational data. A subset of parameters with strong correlation with actuator states can be filtered out. The T-S fuzzy model was used to extract fuzzy diagnostic rules. Experience based on actuator simulation data verifies that the model can be effectively adapted to the actuator’s diagnostic logic and is competent for actuator troubleshooting tasks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Failure analysis

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Switching Event-Triggered control of Nonlinear Parabolic PDE Systems via Galerkin/Neural-Network-Based Modeling Approach

arXiv

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arXiv 2024年

作者： Sun, Xiao-Yu Zhang, Chuan Wu, Huai-Ning Zhang, Xian-Fu School of Mathematical Sciences Qufu Normal University Qufu273165 China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Hangzhou International Innovation Institute Beihang University Hangzhou311115 China School of Control Science and Engineering Shandong University Jinan250061 China

This paper focuses on switching event-triggered output feedback control for a class of parabolic partial differential equation (PDE) systems subject to unknown nonlinearities and external bounded disturbance. Initially, the PDE systems is properly separated into a finite-dimensional ordinary differential equation (ODE) slow system and an infinite-dimensional ODE fast system based on Galerkin technique, especially the slow system can characterize the dominated dynamics. Then, a three-layer neural network is employed to approximate the unknown nonlinearities, and Levenberg-Marquardt algorithm is adopted to get a relative accurate slow system. Subsequentaly, a switching event-triggered control scheme is developed, and a waiting time subject to the triggered condition is implemented to avoid the Zeno behavior and convert the slow system into a switching system. In the following, the stability and H∞ performance issues of the closed-loop system are discussed, and the controllers are displayed in terms of bilinear matrix inequalities (BMIs). Novel algorithms are proposed to convert the BMIs into linear matrix inequalities (LMIs). Additionally, a sub-optimal switching event-triggered controller is obtained using an iterative optimization approach based on LMIs. Finally, simulation on the catalytic rod reaction model and traffic flow model demonstrate the effectiveness of switching event-triggered control strategy. Copyright © 2024, The Authors. All rights reserved.

关键词： Multilayer neural networks

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Data-Driven Tracking control for Non-Affine Yaw Channel of Helicopter via Off-Policy Reinforcement Learning

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IEEE Transactions on Aerospace and Electronic Systems 2025年第3期61卷 7725-7737页

作者： Zhang, Kun Luo, Shijie Wu, Huai-Ning Su, Rong The School of Astronautics Beihang University Beijing100191 China The Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Hangzhou International Innovation Institute Beihang University Hangzhou311115 China The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore

This paper presents an off-policy tracking control scheme for the continuous-time non-affine yaw channel of unmanned aerial vehicle helicopter (UAVH). Firstly, the paper constructs an affine augmented system (AAS) within a parallel control structure to convert the original non-affine tracking error dynamics into affine dynamics. Secondly, the paper derives a stability criterion linking the non-affine system and the AAS, demonstrating that the obtained zero-sum policy from the AAS can achieve the H ∞ performance of the non-affine system. Thirdly, a data-driven off-policy tracking algorithm is designed for approximating the zero-sum solution of the Hamilton-Jacobi-Isaacs equations with unknown dynamics. Moreover, the recursive least squares process with a variable forgetting factor is employed to update the actor-critic neural network (NN) weights, with the algorithm's convergence being proven. Then, the uniformly ultimately bounded (UUB) of tracking errors is guaranteed. Finally, two application examples are offered in simulation to validate the effectiveness of this presented method. © 1965-2011 IEEE.

关键词： Stability criteria

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Neuroadaptive Bipartite Consensus control for Uncertain Networked Agent Systems Subject to Actuator Attacks

Neuroadaptive Bipartite Consensus Control for Uncertain Netw...

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Chinese Automation Congress (CAC)

作者： Yulin Kang Menzji Shi Kexiang Wang Long You Jianzfeng Yue Boxian Lin Kaiyu Qin School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu China National Laboratory on Adaptive Optics Chengdu China Chinese Aeronautical Establishment Beijing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Uncertainties, such as modeling inaccuracies, external disturbances, and actuator attacks are widely spread in the control channels of the networked networked agent system, which affect the accuracy and reliability of the cooperative control to a certain extent. With this in mind, this paper focuses on the robust bipartite consensus control problem of uncertain nonlinear networked networked agent systems subject to actuator attacks. In particular, the communication topology among agents is described by a signed graph, which contains not only cooperative interactions but also competitive interactions among agents. Theoretically, the neural network-based robust consensus controller is designed. On the one hand, compound uncertainties, like modeling inaccuracies and external disturbances are approximated by interpolated fitting of Gaussian radial basis functions. The adaptive laws for approximate parameters are generated online based on the stability conditions of the closed-loop error system. On the other hand, the estimation of the unknown actuator attack factor is achieved based on the adaptive control technique, which results in the effective compensation of the attack-induced control attenuation. Finally, the effectiveness of the proposed robust consensus control scheme is validated using some simulation examples.

关键词： Hands Actuators Adaptation models Uncertainty Consensus control Attenuation Stability analysis Robustness Topology Compounds

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Event-Triggered-Based Privacy-Preserving Finite-Time Flocking control for Networked Multi-Agent Systems

Event-Triggered-Based Privacy-Preserving Finite-Time Flockin...

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IEEE Conference on Decision and control

作者： Jiangfeng Yue Kaiyu Qin Jinliang Shao Mengji Shi Weihao Li Wei Xing Zheng School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China School of Computer Data and Mathematical Sciences Western Sydney University Sydney NSW Australia

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Drawing inspiration from the dynamics of biological groups, flocking behavior has captivated interest due to its adaptive, self-organizing, and resilient characteristics. However, the presence of numerous agents in an open network environment raises concerns regarding the potential for information leakage during flocking movements. To address this issue, we present a decentralized output mapping function, executed independently by each individual agent, to ensure the maintenance of flocking behavior, including velocity alignment, cohesion and collision avoidance. Additionally, to enhance resource efficiency and convergence speed, an event-triggered mechanism is employed to mitigate the excessive consumption of bandwidth and computation resources in traditional flocking control algorithms. Moreover, the designed finite-time controller facilitates rapid convergence of flocking behavior. Finally, the efficacy of our proposed approach is corroborated through numerical simulation experiments.

关键词： Privacy Event detection System performance Bandwidth Numerical simulation Stability analysis Trajectory Optimization Numerical stability Convergence

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A Multi-UAV Formation Obstacle Avoidance Method Combined Improved Simulated Annealing and Adaptive Artificial Potential Field

arXiv

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arXiv 2025年

作者： Ma, Bo Ji, Yi Fang, Liyong School of Aeronautics and Astronautics University of Electronic Science and Technology of China Sichuan Chengdu611731 China SDU-ANU Joint Science College Shandong University Weihai264209 China University of Electronic Science and Technology of China Zhejiang Huzhou3130001 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu611731 China National Key Laboratory of Adaptive Optics Sichuan Chengdu611731 China

The traditional Artificial Potential Field (APF) method exhibits limitations in its force distribution: excessive attraction when UAVs are far from the target may cause collisions with obstacles, while insufficient attraction near the goal often results in failure to reach the target. Furthermore, APF is highly susceptible to local minima, compromising motion reliability in complex environments. To address these challenges, this paper presents a novel hybrid obstacle avoidance algorithm—Deflected Simulated Annealing–Adaptive Artificial Potential Field (DSA-AAPF)—which combines an improved simulated annealing mechanism with an enhanced APF model. The proposed approach integrates a Leader-Follower distributed formation strategy with the APF framework, where the resultant force formulation is redefined to smooth UAV trajectories. An adaptive gravitational gain function is introduced to dynamically adjust UAV velocity based on environmental context, and a fast-converging controller ensures accurate and efficient convergence to the target. Moreover, a directional deflection mechanism is embedded within the simulated annealing process, enabling UAVs to escape local minima caused by semi-enclosed obstacles through continuous rotational motion. The simulation results, covering formation reconfiguration, complex obstacle avoidance, and entrapment escape, demonstrate the feasibility, robustness, and superiority of the proposed DSA-AAPF algorithm. Copyright © 2025, The Authors. All rights reserved.

关键词： Simulated annealing

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The Effects of Spatially-Informed Alarm Types and Presentation Rates on Pilot Performance

The Effects of Spatially-Informed Alarm Types and Presentati...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Ke Zhu Yaning Li Yiyan Wang Jingze Tian Jianwei Huang Wenjun Yang Yafeng Niu School of Mechanical Engineering Southeast University Nanjing China Xiamen Municipal Smart City Technology Co. Ltd. Xiamen China National Key Laboratory of Science and Technology on Aircraft Control Xi'an China

The efficiency of human-machine systems mainly constrains situational awareness in modern air combat. This study aims to investigate the effects of alarm types with spatial information (voice alarms, auditory icon alarms, earcon alarms) on pilot performance and cognitive workload at different alarm presentation rates (low, medium, high) in aircraft operations. Research findings suggest that alarm presentation rate and alarm type have no significant impact on flight performance, while reaction time decreases as the alarm presentation rate increases. When exposed to earcon alarms and auditory icon alarms, participants reaction speed significantly faster compared to voice alarms, with no significant difference between visual and earcon alarms. Furthermore, the study revealed that visual alarms impose a higher cognitive load on participants. These research conclusions can contribute to the rational design of sound alarm in future fighter cockpit systems.

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