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Data-Driven Learning and control with Event-Triggered Measurements

IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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Combat Intention Recognition of Aerial Battlefield Targets Based on LSTM 3rd

Combat Intention Recognition of Aerial Battlefield Targets B...

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

作者： Xu, Hongfeng Zhao, Jiajia Zhang, Hang Jiang, Jixiang Chen, Linxiu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819710867

In the course of military operations, the battlefield situation changes rapidly, and the combat time is fleeting. How to quickly and accurately identify the enemy’s combat intention is one of the important preconditions to ensure the commander’s correct command decision and obtain the initiative in the battlefield. In this paper, aiming at the problems of low accuracy and insufficient algorithm robustness of traditional target combat intention recognition methods in air battlefield, a combat intention recognition method based on LSTM is proposed according to the characteristics of sequence and multi-dimension of target characteristic data. Based on the historical and current state characteristics, electromagnetic characteristics and action characteristics of the target obtained by the sensor, the method uses the LSTM network to build the target combat intention recognition model, and learns the changes of the target characteristics through the network model to realize the target combat intention recognition. Simulation results show that the proposed method can effectively improve the accuracy of target combat intention recognition. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Military operations

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Relative Navigation of Unmanned Aerial Vehicles Based on Data Link Ranging and Partial Guidance Information 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Wang, Ziwen Song, Chuang Hao, Mingrui Liang, Xinkai Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819733323

ISBN: (纸本)9789819733316

In GNSS-denied environments, precise relative navigation between unmanned aerial vehicles (UAVs) is a key technology for achieving cooperative tasks. The relative navigation method based on data link ranging information combines altitude, airspeed measurements, and attitude information to ensure the observability of UAVs’ relative states. However, due to the significant constraints imposed by observability conditions, a novel approach is proposed that utilizes partial guidance information from the UAV swarm towards the target as additional measurements. This approach enhances the observability capability of relative navigation and alleviates the constraints imposed by the observability conditions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Observability

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Multi-UAV Cooperative Path-Planning under complex Threat Environment 42

Multi-UAV Cooperative Path-Planning under Complex Threat Env...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Zhenchang Liu, Yuting Zhao, Hongyin Lu, Hanchen Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789887581543

This paper proposes a cooperative path-planning method based on multi-Dubins path segments to meet the penetration requirements of UAVs in a complex threat environment. A pruning strategy is used in path-planning to sift path segments, and the diversity of threat avoidance paths is considered under a reasonable calculation amount. A threat intrusion strategy is designed for no safety path condition, which makes the cooperative path-planning method have excellent robustness. A cooperative path optimization method based on particle swarm optimization is adopted for the path length and collision avoidance requirements. The simulation results show that the UAV cooperative paths can avoid the threat area under any starting and ending points, and path lengths are close to the expected length. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Unmanned aerial vehicles (UAV)

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Cooperative Formation control of Fixed-Wing UAV Based on L1 Guidance Law Considering Collision Avoidance 7th

Cooperative Formation Control of Fixed-Wing UAV Based on L1 ...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Yue, Keyuan Hao, Mingrui Zhen, Yan Liu, Xinyu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819733392

This article proposes a formation control scheme based on L1 guidance law for fixed wing unmanned aerial vehicle clusters while considering collision avoidance issues between them. The fixed wing aircraft cluster adopts L1 guidance and tracking method to track their respective desired waypoints. By controlling the speed of the fixed-wing UAVs, the entire cluster forms a formation configuration on their individual desired trajectories. During the formation and transformation processes, an improved artificial potential field method is proposed based on the characteristics of fixed-wing UAVs to achieve collision avoidance between clusters. The effectiveness of the proposed approach is validated through numerical simulations based on a six-degree-of-freedom nonlinear UAV model, providing a reference for practical engineering applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Fixed wings

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Target Tracking Method Based on LSTM-EKF 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Xu, Hongfeng Zhao, Jiajia Zhang, Hang Jiang, Jixiang Chen, Linxiu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819733323

ISBN: (纸本)9789819733316

With the development of science and technology, target tracking technology has been widely used in many fields. Through target tracking technology, the accurate estimation of target state can be obtained, and the perception ability can be effectively improved. However, due to the increasing maneuvering ability of the target, the traditional target tracking algorithm is more and more difficult to meet the requirements of maneuvering target tracking. This article in view of the traditional filtering algorithm based on bayesian theory problems of nonlinear error model, in combination with the advantages of EKF and deep learning, introducing the idea of hybrid data model, puts forward the algorithm of target tracking based on LSTM - EKF, and design a mathematical simulation experiment on the performance of the algorithm is verified. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Target tracking

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Multi-scale Visual Feature Association Based Long-Term UAV Positioning Algorithm 1

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

作者： Xiaozu, Li Jiajia, Zhao Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819710874

ISBN: (纸本)9789819710867

In order to solve the long-term drift of positioning in UAVs, we propose a multi-scale visual feature association algorithm, and applied in SLAM systems. Through the upward fusion mechanism, we fuse the image features extracted by the 30-degree angle for FOV and 120-degree angle for FOV, making full use of the ability to perceive global features in the wide FOV and the ability to perceive environmental details in the small FOV. Combined with IMU Sensors, we effectively suppress the positioning drift and improve the accuracy of the SLAM system. Using OSG to render the 3D real scene of Hong Kong, we obtain 3 trajectories in the environment including residential areas, city centers, bay highways, coastlines and mountains to test the algorithm. The experimental results show that the positioning error of the multi-scale visual feature association algorithm does not exceed 0.01% under extreme conditions such as the UAV flight trajectory length surpassing 10,000 m, sharp turn, and high speed, which proves that the algorithm in this paper can ensure the measurement accuracy of the positioning and effectively suppress drift of positioning, and has strong robustness. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Unmanned aerial vehicles (UAV)

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A Review of Target Association Methods 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Xu, Hongfeng Zhao, Jiajia Zhang, Hang Jiang, Jixiang Chen, Linxiu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819733361

ISBN: (纸本)9789819733354

With the continuous development of information technology, target association technology has been more and more widely used in military and civilian fields. How to achieve effective and reliable target data association has always been a difficult and hot spot in the field of target tracking. In this paper, the research status of target association technology is summarized, the existing target association algorithm is sorted and summarized according to the method principle, and the existing problems in the research of target association technology are analyzed, and the further research direction is prospected. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Target tracking

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Review of Numerical Algorithms for Aircraft Trajectory Optimization 3rd

Review of Numerical Algorithms for Aircraft Trajectory Optim...

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

作者： Jiang, Yunfei Liu, Jin Li, Fengyi Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819711062

Flight trajectory optimization is a crucial aspect of aircraft design, and the numerical algorithms for trajectory optimization have always been a hot and challenging topic in domestic and international research. Starting from the classical classification of trajectory optimization methods and combining with recent advancements in the field of trajectory optimization, this paper provides an overview of various numerical algorithms for flight trajectory optimization, including their principles and applications. Furthermore, the characteristics of different methods and their suitability for solving specific problems are analyzed, offering valuable insights for the practical application of optimization methods. Finally, a brief analysis of the development of trajectory optimization is presented, along with a prospective outlook on the future direction of flight trajectory optimization algorithms. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Numerical methods

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Application of Generative Artificial Intelligence GPT in Unmanned Aircraft systems 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Liu, Xinyu Hao, Mingrui Fan, Yu Li, Fengyi Zhen, Yan Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819733361

ISBN: (纸本)9789819733354

This article focuses on the application of generative artificial intelligence technology in unmanned aircraft systems. In detail, it elaborates on the application scenarios of GPT in aircraft design, development and production, aircraft intelligent situational awareness, and aircraft autonomous decision-making. Then article points out the basic conditions for deploying generative artificial intelligence technology in unmanned aircrafts, such as software and hardware requirements, and large-scale databases. At the same time, this article summarizes several inspirations of the intelligent development of unmanned aircrafts and puts forward some prospects for combining generative artificial intelligence technology with aircrafts. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Decision making

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