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Chinese control Conference (CCC)

作者： Yuxuan Wang Liping Yan Zihang Feng Yuanqing Xia Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China

The tracker based on Siamese neural network is currently a technical method with high accuracy in the tracking field. With the introduction of transformer in the visual tracking field, the attention mechanism has gradually emerged in tracking tasks. However, due to the characteristics of attention operation, Transformer usually has slow convergence speed, and its pixel-level correlation discrimination in tracking is more likely to lead to overfitting, which is not conducive to long-term tracking. A brand new framework FAT was designed, which is the improvement of MixFormer. The operation for simultaneous feature extraction and target information integration in MixFormer is retained, and the Mixing block is introduced to suppress the background as much as possible before the information interaction. In addition, a new operation is designed: the result of region-level cross-correlation is used as a guidance to help the learning of pixel-level cross-correlation in attention, thereby accelerating the model convergence speed and enhancing the model generalization. Finally, a joint loss function is designed to further improve the accuracy of the model. Experiments show that the presented tracker achieves excellent performance on five benchmark datasets.

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Towards Pose Estimation for Large UAV in Close Range

Towards Pose Estimation for Large UAV in Close Range

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Youth Academic Annual Conference of Chinese Association of automation (YAC)

作者： Ni Ou Junzheng Wang Shangfei Liu Jiehao Li State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665465373

This paper deals with the problem of 4D pose estimation for large unmanned aerial vehicles (UAVs) in close range. A sensor system consisting of one single point laser range-finder and two cameras is designed and a novel pose estimation method based on vision fusion and point cloud registration is proposed. Our approach works on one-shot mode and only requires 10 samples with real poses for template construction. Through V-rep simulation environment, we generate two 200-sample datasets of different difficulty for evaluation. Error quantiles, 5cm5deg and 10cml0deg are three evaluation metrics used in our ablation experiments. It is illustrated that our method outperforms in robustness and precision due to proposed dimension extension modification and fusion of vision sensors.

关键词： Point cloud compression Measurement Cloud computing Pose estimation Vision sensors Autonomous aerial vehicles Laser modes

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Improved Interpolation with Sub-Pixel Relocation Method for Strong Barrel Distortion

SSRN

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SSRN 2022年

作者： Yuwen, Xuan Zhang, Silong Chen, Long Zhang, Hui School of Transportation Science and Engineering Beihang University Beijing102206 China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

In this paper, we propose an improved interpolation method with sub-pixel relocation method to correct fisheye images with strong barrel distortion. The proposed method takes as inputs the fisheye image and the projection model, and outputs the corrected perspective image. In the method, we project the fisheye image pixels to perspective image plane using the backward projection. The projected pixels are treated as scatter data and their location is refined by the sub-pixel relocation method. The method is designed to aim at the subpixel bias phenomenon of the projected *** sub-pixel relocation method relocates the projected pixel centers to the centers of the projected pixels. Then the relocated points are meshed by the Voronoi diagram method to select the neighbors of the interpolation points. The weights of the neighbors are calculated using the inverse distance method. The index of the neighbor and their weights are stored in a look-up-table structure for reutilization. For each fisheye image, the proposed method can quickly find the neighbors of the interpolation points and the weight of each neighbor through the look-up-table. Test results illustrate that the proposed method achieves the best accuracy among the tested method for fisheye images with strong barrel distortion. © 2022, The Authors. All rights reserved.

关键词： Interpolation

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Dynamic collision avoidance for cooperative fixed-wing UAV swarm based on normalized artificial potential field optimization

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Journal of Central South University 2021年第10期28卷 3159-3172页

作者： LIU Wei-heng ZHENG Xin DENG Zhi-hong State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China China Aerospace Science and Industrial Corporation Beijing 100048China

Cooperative path planning is an important area in fixed-wing UAV ***,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic ***,a normalized artificial potential field optimization is proposed by reconstructing a novel function with anisotropy in each dimension,which can make the flight speed of a fixed UAV swarm independent of the repulsive/attractive gain coefficient and avoid trapping into local optimization and local ***,taking into account minimum velocity and turning angular velocity of fixed-wing UAV swarm,a strategy of decomposing target vector to avoid moving obstacles and pop-up threats is ***,several simulations are carried out to illustrate superiority and effectiveness.

关键词： fixed-wing UAV swarm cooperative path planning normalized artificial potential field dynamic obstacle avoidance local optimization

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Novel sliding-mode disturbance observer-based tracking control with applications to robot manipulators

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Science China(Information Sciences) 2021年第7期64卷 80-91页

作者： Tairen SUN Long CHENG Zengguang HOU Min TAN School of Electrical and Information Engineering Jiangsu University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences

This paper proposes a sliding-mode disturbance observer(SMDOB)-based tracking controller for a class of nonlinear systems with modeling uncertainties and external disturbances. The SMDOB is constructed using an extended state observer embedded by a filtered sliding mode term. The chattering caused by the sliding mode is compressed by the frequency bandwidths of both the extended state observer and the control system. The novelties of the proposed controller are as follows:(1) The semiglobal asymptotical stability of the combined controller-observer system is guaranteed without the boundedness assumption of the time derivatives of modeling uncertainties;(2) the SMDOB can be implemented with a low complexity because of only three parameters to be tuned. Applications to robot manipulators illustrate the effectiveness of the SMDOB-based tracking control strategy.

关键词： adaptive control robot manipulator disturbance observer sliding mode

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Accelerating Realistic Multi-Route Traffic Flow Generation Based on Improved Simulated Annealing Algorithms

Accelerating Realistic Multi-Route Traffic Flow Generation B...

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International Conference on Intelligent Transportation

作者： Hongrui Chen Yan Zhang Xingyuan Dai Jiaming Sun Fei Cong Yanan Lu Bingji Xu Yisheng Lv School of Information Engineering China University of Geosciences (Beijing) Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China China Telecom Digital City Technology Co. Ltd Hebei China

In the traffic simulation system, the data quality and inference speed of traffic flow generation have a direct impact on the correlation between analysis results and actual traffic conditions, as well as the efficiency of utilization. Existing traffic flow generation methods often rely on abundant sensor data and involve time-consuming generation processes. To reduce time costs, in this paper, we propose an efficient Multi-Route Traffic Flow Generator (MTFG). The generation process is divided into two parts: multi-route generation and route quantity search. In the multi-route generation, we employ a Multi-Route Generator (MRG) methodology leveraging topological road network data to generate distinct traffic routes for identical origin-destination pairs. This ensures the attainment of diversified vehicle trajectories even within a sparsely equipped detector network. Subsequently, in the route quantity search, we employ an improved simulated annealing algorithm to systematically explore the traffic route quantity based on the generated multiple routes, thereby significantly amplifying the algorithm's efficacy in route generation. We validate the effectiveness of MTFG using the Malaga open dataset on the SUMO simulation platform. Compared to the strong baseline Flow Generator Algorithm (FGA) with a training time exceeding 2.5h, MTFG achieves the target metric in just 1h under the same conditions, saving over 55% of training time.

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Maximum power point tracking of photovoltaic array based on improved Particle Swarm Optimization Algorithm 4

Maximum power point tracking of photovoltaic array based on ...

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2022 4th International Conference on Energy systems and Electrical Power, ICESEP 2022

作者： Lai, GuangZhi Li, HaoRan Zhang, ChangZhi Zhang, YiHao Wang, ZhiJin State Grid e-commerce Co. Ltd Beijing10053 China State Grid Tianjin Electric Power Company China School of Automation Southeast University Jiangsu Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

With the vigorous development of the photovoltaic industry, how to improve the efficiency of photovoltaic power generation has become an important issue, among which partial shadow occlusion is an important reason affecting the efficiency. The efficiency of photovoltaic power generation can be effectively improved by adopting the maximum power point tracking method (MPPT), but the traditional MPPT method is not ideal in the partial shadow occlusion of the photovoltaic array. To solve this problem, this paper proposes an improved particle swarm optimization method to effectively improve the tracking efficiency of MPPT when multiple peaks appear in the photovoltaic arrays power curve (P-V) under the partial shadow. The proposed method improves the learning factor of the traditional particle swarm optimization algorithm and designs the initial position of the particles according to the characteristics of the photovoltaic array. By adding the particle elimination mechanism, the number of particles changes dynamically, and the tracking speed of the algorithm for the maximum power of the photovoltaic array is improved. Through the result of the simulation, it is not difficult to get the conclusion that the improved particle swarm optimization algorithm can effectively improve the performance of the photovoltaic system under partial shadows. © 2022 institute of Physics Publishing. All rights reserved.

关键词： Efficiency

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An Aeromagnetic Compensation Algorithm Based on Broad Learning System

An Aeromagnetic Compensation Algorithm Based on Broad Learni...

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Robotics, Artificial Intelligence and Intelligent control (RAIIC), International Conference on

作者： Qilong Wang Junlei Song Chao Zuo Kaifeng Dong Fang Jin School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo- Exploration Ministry of Education Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China

ISBN: (数字)9798350352627

ISBN: (纸本)9798350352634

Aeromagnetic surveys, renowned for their operational flexibility and high efficiency, serve as a crucial technique for measuring the geomagnetic field. However, aeromagnetic surveys are easily affected by magnetic interference from navigation platforms, making the compensation of aeromagnetic interference a crucial step in the measurement process. To address the inadequate consideration of nonlinear magnetic field interference in traditional compensation algorithms, this paper introduces an aeromagnetic compensation approach based on broad learning system. The broad learning system employs an incremental learning mechanism aimed at enhancing the precision of the network alongside the increase in nodes. With each expansion of the network node, computation is streamlined to calculating the pseudo-inverse of the expansion node, eliminating the necessity for retraining the entire network structure. Leveraging the nonlinear fitting characteristics of the broad learning system, this paper improves the accuracy of aeromagnetic interference compensation. Through UAV flight experiments, the broad learning system is compared with methodologies using particle swarm optimization (PSO) and BP neural network. Compared with PSO, training time was reduced by $21.3 \%$ and magnetic interference by $33.6 \%$. Compared with BP neural networks, training time was reduced by $34.9 \%$ and magnetic interference by $28.6 \%$. This paper provides references and ideas for the selection of aeromagnetic interference compensation algorithms.

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Fault Detection and Isolation for Multi-agent systems Under Event-Triggered Communication: A Zonotopic Joint Estimation Method

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IEEE Internet of Things Journal 2025年

作者： Tian, Mingliang Guo, Zhihua Wang, Xing Niu, Ben Wang, Xinjun Wang, Ding Wang, Huanqing Shandong Normal University School of Information Science and Engineering Jinan250014 China Beijing University of Technology Faculty of Information Technology Beijing100124 China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China Bohai University Department of Mathematical Science AndAutomatization Institute Jinzhou121000 China

This paper investigates the fault detection and isolation problem of a class of leader-follower multi-agent systems subject to unknown-but-bounded disturbances under an event-triggered communication mechanism (ETCM). Firstly, an adaptive ETCM is proposed to avoid the continuous acquisition of outputs from neighboring agents, thereby reducing the communication burden. Secondly, a joint state and fault observer is designed, and H∞ analysis is utilized to improve the robustness of the observer against external disturbances and event-triggered errors. Next, zonotopic reachability analysis is utilized to derive the estimated intervals of the system state and fault signal, based on which a fault detection and isolation method is developed to determine both when the system is faulty and which agent is at fault. Finally, a fighter formation model is employed to verify the effectiveness of the proposed approach. © 2014 IEEE.

关键词： Multi agent systems

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Disturbance Rejection for Pedaling Rehabilitation Robot Based on Integration of Equivalent-Input-Disturbance and Repetitive control Methods 32

Disturbance Rejection for Pedaling Rehabilitation Robot Base...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Zhou, Yujian She, Jinhua Wang, Feng Iwasaki, Makoto School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Tokyo University of Technology School of Engineering Tokyo Hachioji192-0982 Japan Nagoya Institute of Technology Department of Electrical and Mechanical Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350399714

This study integrated an improved equivalent-input-disturbance (EID) and a repetitive control methods to ensure reference tracking and enhance disturbance-rejection performance for a pedaling rehabilitation robot. A repetitive controller ensures steady-state tracking of a periodic reference input. An EID estimator with a state observer estimates and compensates for the effect of disturbances generated by patients with lower-limb impairment. The stability condition of the closed-loop system is analyzed based on the Lyapunov stability theory. Simulation results show the effectiveness of this method. © 2023 IEEE.

关键词： Disturbance rejection

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