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H∞ fault-tolerant fuzzy intermittent control for nonlinear hyperbolic PDE systems with multiple delays and actuator failures

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ISA Transactions 2025年 156卷 39-60页

作者： Zhang, Xu Gao, Xuan Wang, Zi-Peng Luo, Biao Han, Ke-Zhen Yan, Xue-Hua School of Automation Central South University Changsha410083 China School of Electrical Engineering University of Jinan Jinan250022 China School of Information Science and Technology Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System and Beijing Institute of Artificial Intelligence Beijing University of Technology Beijing100124 China

This study presents an H∞ fault-tolerant fuzzy intermittent control approach for the nonlinear hyperbolic partial differential equation (PDE) systems with multiple delays and actuator failures (MDAFs). Firstly, the nonlinear hyperbolic PDE systems with MDAFs are characterized by the Takagi–Sugeno (T–S) fuzzy delayed hyperbolic PDE model. Next, by employing the Lyapunov direct method, this paper demonstrates the robust exponential stability using spatial linear matrix inequalities (SLMIs) based on a new switching Lyapunov functional (LF). Furthermore, the H∞ fault-tolerant fuzzy intermittent control issue for nonlinear hyperbolic PDE systems with MDAFs is transformed into the LMI feasibility problem to deal with the SLMIs. Lastly, the feasibility of the constructed control strategy is demonstrated by two illustrative examples. © 2024 International Society of automation

关键词： Lyapunov functions

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Synthesis of Decoherence-Free Modes in Linear Quantum Passive systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Miao, Zibo Pan, Yu Gao, Qing School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms Shenzhen518055 China The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique. © 2024 IEEE.

关键词： Poles

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A new noise network and gradient parallelisation‐based asynchronous advantage actor‐critic algorithm

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IET Cyber-systems and Robotics 2022年第3期4卷 175-188页

作者： Zhengshun Fei Yanping Wang Jinglong Wang Kangling Liu Bingqiang Huang Ping Tan Provincial Key Institute of Robotics School of Automation and Electrical EngineeringZhejiang University of Science and TechnologyHangzhouChina State Key Lab of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhouChina

Asynchronous advantage actor‐critic(A3C)algorithm is a commonly used policy opti-mization algorithm in reinforcement learning,in which asynchronous is parallel inter-active sampling and training,and advantage is a sampling multi‐step reward estimation method for computing *** order to address the problem of low efficiency and insufficient convergence caused by the traditional heuristic exploration of A3C algorithm in reinforcement learning,an improved A3C algorithm is proposed in this *** this algorithm,a noise network function,which updates the noise tensor in an explicit way is constructed to train the *** advantage estimation(GAE)is also adopted to describe the dominance ***,a new mean gradient parallelisation method is designed to update the parameters in both the primary and secondary networks by summing and averaging the gradients passed from all the sub‐processes to the main *** experiments were conducted in a gym environment using the PyTorch Agent Net(PTAN)advanced reinforcement learning library,and the results show that the method enables the agent to complete the learning training faster and its convergence during the training process is *** improved A3C algorithm has a better performance than the original algorithm,which can provide new ideas for sub-sequent research on reinforcement learning algorithms.

关键词： asynchronous advantage actorcritic (A3C) generalised advantage estimation (GAE) parallelisation reinforcement learning

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Tilt Tri-Rotor UAV Attitude control in Hover Mode

Tilt Tri-Rotor UAV Attitude Control in Hover Mode

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Ma, Yan Wang, Yingxun Zhao, Jiang Cai, Zhihao Liu, Ningjun School of Automation Science and Electrical Engineering Beihang University Beijing100083 China Institute of Unmanned System Beihang University Beijing100083 China

ISBN: (纸本)9789811966125

This paper studied a tilt tri-rotor UAV (Unmanned Aerial Vehicle) attitude control in hover mode. Firstly, the mathematical model of the tilt tri-rotor UAV is established, in which the propeller forces and moments are analyzed and calculated. On this basis, the attitude dynamic equations are obtained. The mathematical model is used for attitude controller design. Secondly, a backstepping based control scheme is designed for the tilt tri-rotor UAV attitude control, and tracking differentiator (TD) is adopted to improve the control performance of basic backstepping control approach. On this basis, roll, pitch, and yaw angle controllers are designed. Also, different kinds of disturbances are considered, and PID (Proportion-Integral-Differential) controllers are used for comparison. Finally, comparative simulations are carried out by using MATLAB, and the performance of the attitude control system is tested. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Attitude control

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Positioning Method for Covered Vehicles Based on Neutrino Detection and Reinforcement Learning 3

Positioning Method for Covered Vehicles Based on Neutrino De...

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3rd International Conference on Electronic Information engineering and Computer, EIECT 2023

作者： Han, Mingren Gao, Jiashan Zhou, Peng Zhang, Yixin Beijing Institute of Control Engineering China Academy of Space Technology Beijing China Beihang University School of Automation Science and Electrical Engineering Beijing China

ISBN: (纸本)9798350357707

In complex environments like underwater or underground, traditional navigation technologies face limitations due to the restricted penetration of optical and radio signals. Neutrino signals, which have extremely strong penetration capabilities, offer a new possibility. This study explores the challenges of navigation and positioning of covered vehicles and proposes a neutrino-based navigation and positioning technology to overcome the limitations of traditional navigation technologies in complex environments. This research combines reinforcement learning methods and Kalman filters, using the Proximal Policy Optimization (PPO) algorithm to tune the parameters of the Kalman filter to improve navigation and positioning accuracy. In the study, a Kalman filter estimation system model for vehicles in navigation signal denied environment environments was first established, then a navigation and positioning method based on neutrino detection was designed, and finally, a parameter adaptive PPO Extended Kalman Filter (PPOEKF) state estimation method was proposed. Through mathematical simulation and comparative analysis, the research results show that using reinforcement learning methods to tune the parameters of the Kalman filter can improve the accuracy of navigation and positioning, especially in complex environments. © 2023 IEEE.

关键词： Reinforcement learning

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Novel vision-LiDAR fusion framework for human action recognition based on dynamic lateral connection

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IET Cyber-systems and Robotics 2024年第4期6卷 21-31页

作者： Fei Yan Guangyao Jin Zheng Mu Shouxing Zhang Yinghao Cai Tao Lu Yan Zhuang The School of Control Science and Engineering Dalian University of TechnologyDalianChina Technology Centre of Dalian Customs Dalian CustomsDalianChina ZX‐YZ School of Network Science Haikou University of EconomicsHainanChina The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijingChina

In the past decades,substantial progress has been made in human action ***,most existing studies and datasets for human action recognition utilise still images or videos as the primary ***-based approaches can be easily impacted by adverse environmental *** this paper,the authors propose combining RGB images and point clouds from LiDAR sensors for human action recognition.A dynamic lateral convolutional network(DLCN)is proposed to fuse features from *** RGB features and the geometric information from the point clouds closely interact with each other in the DLCN,which is complementary in action *** experimental results on the JRDB-Act dataset demonstrate that the proposed DLCN outperforms the state-of-the-art approaches of human action *** authors show the potential of the proposed DLCN in various complex scenarios,which is highly valuable in real-world applications.

关键词： neural network-based pedestrian identification sensor fusion

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Robust Coordinated Longitudinal control of MAV Based on Energy State

Robust Coordinated Longitudinal Control of MAV Based on Ener...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Zhang, Chenlong Li, Dawei Li, Haodong School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Unmanned System Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

Fixed-wing Miniature Air Vehicle (MAV) is not only coupled with longitudinal motion, but also more susceptible to wind disturbance due to its lighter weight, which brings more challenges to its altitude and airspeed controller design. Therefore, in this paper, an improved longitudinal control strategy based on energy state, is proposed to address the above-mentioned issues. The control strategy utilizes the Linear Extended State Observer (LESO) to observe the energy states and the disturbance of the MAV, and then designs a Multiple-Input Multiple-Output (MIMO) controller based on a more coordinated Total Energy control (TEC) strategy to control the airspeed and altitude of the MAV. The performance of this control strategy has been successfully verified in a Model-in-the-Loop (MIL) simulation with Simulink, and a comparative test with the classical TEC algorithm is carried out. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Longitudinal control

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Impact Time Cooperative Guidance for Multi-Missile system Based on Incremental Learning 42

Impact Time Cooperative Guidance for Multi-Missile System Ba...

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42nd Chinese control Conference, CCC 2023

作者： Li, Xuheng Yu, Jianglong Dong, Xiwang Ren, Zhang Feng, Zhuo Liang, Biao School of Automation Science and Electrical Engineering Beihang University Science and Technology on Aircraft Control Laboratory Beijing100190 China Beijing Institute of Control and Electronic Technology Beijing100038 China

ISBN: (纸本)9789887581543

An impact time cooperative guidance method based on incremental learning is proposed for multi-missile cooperative guidance problem in the attack scenario. Firstly, a guidance model is established to represent the relationship of the missiles and the target. Secondly, an impact time coordinated guidance law based on the consensus method is designed. Then, time-to-go of the missile is predicted using an incremental learning algorithm, so that the accuracy of time-to-go can be better than the results calculated by traditional methods. Finally, the trained neural network is used to predict time-to-go. The results show that the algorithm can be used in the cooperative guidance law to complete the coordination in time, which is superior to the traditional guidance rate in coordination and has advantage in the scene of large maneuvering target. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Learning algorithms

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LiDAR Point Cloud Map Coding Framework Based on Quadric Surface Fitting and Scene Construction 5

LiDAR Point Cloud Map Coding Framework Based on Quadric Surf...

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5th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2024

作者： Sun, Xuebin Wang, Jinxi Yang, Xiaofei School of Electrical Automation and Information Engineering Tianjin University Tianjin China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Shanghai Institute of Optics and Fine Mechanics Department of Aerospace Laser Technology and System Shanghai China

ISBN: (纸本)9798350355925

Due to rapid 3D acquisition advancements, LiDAR point clouds are prevalent in emerging applications like heritage preservation, mobile robotics, and remote sensing. Yet, the sheer data volume poses challenges for transmission and storage, especially in autonomous driving. This paper introduces an efficient coding framework for compressing large dense LiDAR point cloud maps. By recording timestamps and quaternion matrices during map construction, we reduce map compression to sequence compression. The scans are segregated into intra-frames and inter-frames. For intra-frames, a quadric surface fitting intra-prediction technique eliminates spatial redundancy. For inter-frames, by constructing the 3D scene using encoded intra-frames, the inter-frame can be simulated according to its posture and LiDAR intrinsic parameters. Coding focuses on the difference between actual and predicted point cloud data. Decoding reverses this process, reconstructing the point cloud map from the decoded sequence and quaternion matrices. KITTI dataset experiments show the point cloud map can be averagely compressed to 3.43% of its original size while maintaining centimeter-level precision. This outperforms both octree and Google Draco methods. © 2024 IEEE.

关键词： Mobile robots

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Consensus control of Multi-Agent systems Using Fault-Estimation-in-the-Loop:Dynamic Event-Triggered Case

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1440-1451页

作者： Yamei Ju Derui Ding Xiao He Qing-Long Han Guoliang Wei Shanghai Key Lab of Modern Optical System the Department of Control Science and EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia Department of Automation BNRistTsinghua UniversityBeijing 100084China College of Science University of Shanghai for Science and TechnologyShanghai 200093China

The paper develops a novel framework of consensus control with fault-estimation-in-the-loop for multi-agent systems(MASs)in the presence of faults.A dynamic event-triggered protocol(DETP)by adding an auxiliary variable is utilized to improve the utilization of communication ***,a novel estimator with a noise bias is put forward to estimate the existed fault and then a consensus controller with fault compensation(FC)is adopted to realize the demand of reliability and safety of addressed ***,a novel consensus control framework with fault-estimation-in-the-loop is developed to achieve the predetermined consensus performance with the l_(2)-l_(∞)constraint by employing the variance analysis and the Lyapunov stability ***,the desired estimator and controller gains are obtained in light of the solution to an algebraic matrix equation and a linear matrix inequality in a recursive way,***,a simulation result is employed to verify the usefulness of the proposed design framework.

关键词： Consensus control dynamic event-triggered protocol(DETP) fault compensation(FC) fault estimation multi-agent systems(MASs)

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