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Dual and reduced-order observer based attack-free protocols for consensus of multi-agent systems with Markovian switching topologies

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systems & control Letters 2025年 202卷

作者： Tian-Yu Gao Zhao-Yan Li Bin Zhou Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin 150001 China School of Mathematics Harbin Institute of Technology Harbin 150001 China Zhengzhou Research Institute of HIT Zhengzhou 450000 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin 150001 China

This paper studies the output feedback consensus problem of linear multi-agent systems with Markovian switching topologies. To avoid reconstructing the Markovian switching topologies during designing the observers or adding the state of the observers to the information exchange loop, dual and reduced-order observer based attack-free consensus protocols are proposed, which only utilizes the relative outputs of neighboring agents. It is shown that, under certain mild conditions, a necessary and sufficient condition for the solvability of the mean square consensus problem is that the union of switching topologies has a spanning tree. Finally, numerical examples are given to illustrate the effectiveness of the proposed approaches.

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Coverage Path Planning of Multiple Disconnected Convex Polygons Based on Improved Genetic Algorithm 1

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12th China Conference on Command and control, C2 2024

作者： Hu, Tianmi Wang, Shuyue Lyu, Yang Liang, Xinkai Pan, Quan Northwestern Polytechnical University Shaanxi Xi’an710129 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (数字)9789819777747

ISBN: (纸本)9789819777730

This paper considers the energy-constrained multi-UAV multi-area coverage path planning problem which is a generic technology backbone of many survey applications using multiple UAVs. The problem is usually NP-hard and may not be solved efficiently taking into consideration the scale of the areas to survey. In this paper, we present a two-step strategy to solve this problem approximately. In the first step, we compute coverage paths controlled by different enter/exit points for each polygon area. In the second step, we propose a genetic algorithm-based approach to determine the access order of multiple areas while simultaneously determining the entry point for each area. The above problem can be modeled as a variant of the vehicle routing problem (VRP) taking into account the limitation of the maximum flight distance of each UAV. The simulation experiment results indicate that our approach is able to plan proper paths for the multi-UAV multi-area coverage mission, while the energy constraint is satisfied at the same time. © Chinese Institute of Command and control 2024.

关键词： Genetic algorithms

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Linear Quadratic Pursuit and Evasion Differential Game Guidance Strategy with Obstacle Avoidance 34th

Linear Quadratic Pursuit and Evasion Differential Game Guida...

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34th Congress of the International Council of the Aeronautical Sciences, ICAS 2024

作者： Wang, Xintao Yang, Ming Ma, Ping Chao, Tao Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150080 China

In this paper, a class of linear quadratic differential game guidance scheme is presented to study the pursuit and evasion conflict scenario that an evader establishes a static obstacle and performs the evasion maneuver to avoid a pursuer. First of all, the engagement kinematic model among the obstacle, the pursuer, and the evader is linearized according to the assumption. The issue of the pursuit and evasion game is transformed into a linear quadratic differential game through the dead zone and the cost functions. Furthermore, the linear quadratic differential game approach is utilized to obtain the guidance strategy with obstacle avoidance. Numerical simulation results are employed to validate the performance of the guidance policy. © 2024, International Council of the Aeronautical Sciences. All rights reserved.

关键词： Cost functions

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Adaptive optimal output regulation: A parametric Lyapunov equation approach 5

Adaptive optimal output regulation: A parametric Lyapunov eq...

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5th International Conference on control, Robotics, and intelligent system, CCRIS 2024

作者： ul Aabidin Lodhi, Zain Jiang, Huaiyuan Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin China

ISBN: (数字)9781510685871

ISBN: (纸本)9781510685864

This article delves into a data-driven approach for solving the adaptive optimal output regulation problem in continuous-time linear systems with uncertain dynamics. Employing a class of parametric Lyapunov equations in conjunction with a nominal system model, the initial stabilizing feedback gain is determined to initiate the iterative method. Then, by utilizing a policy-iteration-based technique, we design an optimal control policy to achieve precise output tracking and disturbance rejection. The prescribed convergence characteristics of the closed-loop system directly result from the properties embedded within the solution of the parametric Lyapunov equation. The applicability and performance of the proposed method are demonstrated through a numerical example involving an input-constrained double integrator system. © 2024 SPIE.

关键词： Continuous time systems

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EPM-Net: A better way for optical and infrared scene matching via edge point 12

EPM-Net: A better way for optical and infrared scene matchin...

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SPIE 12th International Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2023

作者： Huang, Shixiang Chi, Longyun Fu, Wenxing Tian, Jinwen National Key Laboratory of Multispectral Information Intelligent Processing Technology Huazhong University of Science and Technology Wuhan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

As a crucial auxiliary technique in inertial navigation, scene matching has been widely applied in aircraft navigation and guidance. To enhance the adaptability and efficiency of scene matching algorithms in complex environments, existing approaches have gradually shifted towards heterogeneous scene matching, such as optical/ infrared scene matching based on deep learning features, with a focus on point features. However, due to the complex and diverse nonlinear distortions between optical and infrared images, the matching accuracy often fails to meet the practical requirements of navigation and positioning. In view of this problem, an EPM-Net algorithm based on edge features is proposed to improve matching performance by extracting more stable and discriminative edge point descriptors. Experimental results on infrared datasets demonstrate that this method achieves an average matching accuracy improvement of more than four times compared to traditional and existing deep learning methods. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep learning

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Target Recognition Inference Based on Knowledge Graph and Graph Neural Network

Target Recognition Inference Based on Knowledge Graph and Gr...

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2024 China Automation Congress, CAC 2024

作者： Li, Wei Xu, Hongfeng Li, Yuan Beijing Institute of Technology Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9798350368604

In complex environments with vast and diverse information sources, target recognition serves as a crucial precursor to situational analysis, providing the foundation for further decision-making and analysis. Traditional algorithms for target recognition often rely on human experience and rules, necessitating expert knowledge and subjective judgments, which introduces uncertainties. This paper introduces a method for target recognition inference, leveraging Situation Knowledge Graph Convolutional Neural Network (SKGCN). By employing active and passive radar sensor data in complex scenarios, the algorithm processes inputs within a self-constructed situational knowledge graph. It derives vector representations of target entities through aggregation operations among neighboring nodes and extracts perceptual data vectors using the embedding layer. The algorithm calculates the alignment between sensor data and target entities, facilitating target recognition and inference in complex scenarios. Simulation results confirm the effectiveness of the proposed approach. © 2024 IEEE.

关键词： Knowledge graph

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Aircraft Middle and Final Stage Attitude control on Fully Actuated system Theory

Aircraft Middle and Final Stage Attitude Control on Fully Ac...

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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Xinyu Liu Mingrui Hao Yu Fan Yan Zhen Wendi Sun National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This paper takes the attitude control of the middle and final stages of the aircraft as the research background, and explores a new nonlinear control method for the strong nonlinearity, strong coupling, fast time-varying and uncertainty characteristics of the aircraft. A second-order fully actuated system model of the aircraft is constructed, which is starting from the six degree of freedom mathematical model, including aerodynamic coupling and control coupling. It is a nonlinear model, including roll, yaw and pitch full three channels. Also, the paper designed an attitude controller on fully actuated system, which is based on the PD control method, and proved the stability of the controller through Lyapunov stability analysis method. Then, the controller is integrated into the aircraft simulation, and mathematical simulation verification is carried out under benchmark conditions, achieving good attitude control effect.

关键词： Couplings Attitude control Atmospheric modeling Benchmark testing Mathematical models Stability analysis Aircraft manufacture

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A credibility allocation approach of complex simulation systems 35

A credibility allocation approach of complex simulation syst...

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35th European Modeling and Simulation Symposium, EMSS 2023

作者： Zhang, Huan Li, Wei Geng, HuaPin Ma, Ping Yang, Ming Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150080 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9788885741881

Complex simulation systems usually need to satisfy the credibility requirements and the credibility of complex simulation systems is inextricably linked to the credibility of simulation sub-systems. Hence, in order to guarantee the credibility of complex simulation systems meets requirements, it is necessary to allocate the credibility of simulation sub-systems. Complex simulation systems are composed of several correlative simulation sub-systems and their credibility has correlation relationships, which makes it difficult to obtain the credibility of simulation sub-systems quickly. The existing works mostly ignore the relationships between the sub-systems and are difficult to generate the credibility allocation results of simulation sub-systems. In this paper, we model the credibility allocation problem as a probabilistic inference problem based on the pairwise Markov random field (PMRF). In addition, we apply several inference algorithms to perform the inference exactly and approximately in the credibility PMRF. Finally, experiments are conduted on the air defense combat complex simulation system, and the experiment results demonstrate that the proposed method can obtain the credibility allocation results quickly and accurately. © 2023 The Authors.

关键词： Inference engines

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An Algorithm for Cooperative Navigation Using Neural Network to Identify Colored Noise Online

An Algorithm for Cooperative Navigation Using Neural Network...

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2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Sheng, Danting Cheng, Jin Li, Fengyi Hao, Mingrui Beijing Electro-mechanical Engineering Institute CASIC Beijing China HIWING Technology Academy of CASIC CASIC Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation CASIC Beijing China

ISBN: (纸本)9798350384185

In practical applications of cooperative navigation algorithms based on Kalman filtering, noise is often colored noise, which does not meet the requirement of Gaussian white noise for Kalman ***, an algorithm is proposed to identify and compensate for colored noise online using a BP neural ***, a cooperative navigation model based on Kalman filtering is ***, by studying the update process of Kalman filtering, the neural network is incorporated into the prediction calculation of the observations, following the online learning and updating of the Kalman *** simulations show that under conditions of colored noise, the results of the Kalman filter ***, after correction by the BP neural network, the filtering converges, providing high reference value for improving the accuracy of cooperative navigation. © 2024 IEEE.

关键词： Wiener filtering

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