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Adaptive control of Discrete-time Nonlinear systems Using ITF-ORVFL

IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 556-563页

作者： Xiaofei Zhang Hongbin Ma Wenchao Zuo Man Luo School of Automation Beijing Institute of TechnologyBeijing 100081 School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China School of Automation Beijing Institute of Technologyand also with the State Key Laboratory of Intelligent Control and Decision of Complex Systems(Beijing Institute of Technology)Beijing 100081China School of Automation Beijing Institute of TechnologyBeijing 100081and he is with Beijing Institute of Electronic System EngineeringBeijing 100854China School of Automation Beijing Institute of TechnologyBeijing 100081and she is with Ant GroupBeijing 310013China

Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly *** network structure in which contains the direct links between inputs and outputs is unique,and stability analysis and real-time performance are two difficulties of the control systems based on neural *** this paper,combining the advantages of RVFL and the ideas of online sequential extreme learning machine(OS-ELM)and initial-training-free online extreme learning machine(ITFOELM),a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm(ITF-ORVFL)is investigated for training *** link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed,and the stability for nonlinear systems based on this learning algorithm is *** experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.

关键词： Adaptive control initial-training-free online learning algorithm random vector functional link networks

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Effective distributed algorithm for solving linear matrix equations

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Science China(Information Sciences) 2023年第8期66卷 265-266页

作者： Songsong CHENG Jinlong LEI Xianlin ZENG Yuan FAN Yiguang HONG Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and Automation Anhui University Department of Control Science and Engineering Tongji University Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Dear editor,Solving linear matrix equations is a basic and important problem in many fields such as the computation of generalized inverses of matrices and(generalized) Sylvester equations. Also, the linear algebraic ...

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Visual Explanation of Object Detectors via Saliency Maps 18

Visual Explanation of Object Detectors via Saliency Maps

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Xiao, Jin Liu, Wenrui Hu, Xiaoguang Jiang, Hao Wang, Weipeng Yahang, Li Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing China Beihang University Beijing China The Third Academy of Casic Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350312201

In recent years, rapid progress of deep learning has resulted in object detection algorithms based on deep neural networks nearly completely replacing traditional methods. This shift has led to significant improvements in both accuracy and speed of object detection. However, deep neural networks that support decision-making inobject detection are complex black boxes with hidden internal logic and operations. This lack of transparency results in deep learning models being unexplainable, which limits their practical deployment. In this paper, we analyze the current state and future trends of interpretable technology in object detection and propose an effective object detection interpretable algorithm. This algorithm aims to explain the underlying logic of AI decision-making and provide support for the high performance and credibility of object detection algorithms based on deep neural networks through quantitative evaluation indicators. © 2023 IEEE.

关键词： Object detection

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Multi-UAV Cooperative Target Tracking Strategy Based on Formation control

Multi-UAV Cooperative Target Tracking Strategy Based on Form...

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第三十八届中国控制会议

作者： Duo Wang Zhihong Peng Xiaojie Ju Tao Yu Xue Wang China Academy of Launch Vehicle Technology School of Automation Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology

In this paper we mainly studies the cooperative tracking issue of multi-UAV based on formation control. The theory and method of formation control are introduced in the paper to ensure the continuous and effective ground target tracking results. The tracking targets are regarded as the leader or the structural center of the formation. The multi-UAVs are considered as followers to form an unstable formation system. The formation stability can be maintained by constructing control law to ensure the continuous and effective tracking of intelligent targets by the multi-UAV. The formation control method based on the leader-follower system and the potential function are adopted to ensure the stability of formation consists of UAVs and the target, so that UAVs can keep tracking of the target. We prove the tracking strategy and the formation control results by MATLAB simulation.

关键词： Cooperative target tracking formation control leader-follower system potential function

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MC-NeRF: Multi-Camera Neural Radiance Fields for Multi-Camera Image Acquisition systems

arXiv

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arXiv 2023年

作者： Gao, Yu Su, Lutong Liang, Hao Yue, Yufeng Yang, Yi Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Neural Radiance Fields (NeRF) use multi-view images for 3D scene representation, demonstrating remarkable performance. As one of the primary sources of multi-view images, multi-camera systems encounter challenges such as varying intrinsic parameters and frequent pose changes. Most previous NeRF-based methods assume a unique camera and rarely consider multi-camera scenarios. Besides, some NeRF methods that can optimize intrinsic and extrinsic parameters still remain susceptible to suboptimal solutions when these parameters are poor initialized. In this paper, we propose MC-NeRF, a method that enables joint optimization of both intrinsic and extrinsic parameters alongside NeRF. The method also supports each image corresponding to independent camera parameters. First, we tackle coupling issue and the degenerate case that arise from the joint optimization between intrinsic and extrinsic parameters. Second, based on the proposed solutions, we introduce an efficient calibration image acquisition scheme for multi-camera systems, including the design of calibration object. Finally, we present an end-to-end network with training sequence that enables the estimation of intrinsic and extrinsic parameters, along with the rendering network. Furthermore, recognizing that most existing datasets are designed for a unique camera, we construct a real multi-camera image acquisition system and create a corresponding new dataset, which includes both simulated data and real-world captured images. Experiments confirm the effectiveness of our method when each image corresponds to different camera parameters. Specifically, we use multi-cameras, each with different intrinsic and extrinsic parameters in real-world system, to achieve 3D scene representation without providing initial poses. The Code and supplementary materials are available at https://***/MC-NeRF Copyright © 2023, The Authors. All rights reserved.

关键词： Parameter estimation

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Attitude Calculating for a New Strap-down Inertial Navigation system Based on Angular Accelerometers

Attitude Calculating for a New Strap-down Inertial Navigatio...

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IEEE International Conference on Information and Automation

作者： Meiling Wang Xin Zheng Tong Liu Tonglei Wang Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Beijing Institute of Automatic Control Equipment Beijing China

ISBN: (纸本)9781509041039

This paper introduces an attitude updating method based on a new structure of gyroscope-free inertial navigation system(GFINS), in which the angular accelerometers are used to take the place of gyroscopes. For this new structure of GFINS, a new mathematical model is developed to determine the general three-dimensional motion of body segments. The mathematical model is mainly based on the direction cosine matrix. A second-order differential equation which is represented by angular acceleration should be calculated to solve this problem using the fourth order Runge-Kutta method combining with the interpolation method. Furthermore, the final result of this approach is shown by applying the mathematical model to some simulation data generated by the trajectory generator. The simulation results indicate that the mathematical model has a good performance.

关键词： angular accelerometer attitude updating direction cosine matrix GFINS

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A review of cooperative path planning of an unmanned aerial vehicle group

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Frontiers of Information Technology & Electronic Engineering 2020年第12期21卷 1671-1694页

作者： Hao ZHANG Bin XIN Li-hua DOU Jie CHEN Kaoru HIROTA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081China Department of Computational Intelligence and Systems Science Tokyo Institute of TechnologyTokyo 1528550Japan

As a cutting-edge branch of unmanned aerial vehicle(UAV)technology,the cooperation of a group of UAVs has attracted increasing attention from both civil and military sectors,due to its remarkable merits in functionality and flexibility for accomplishing complex extensive tasks,e.g.,search and rescue,fire-fighting,reconnaissance,and *** path planning(CPP)is a key problem for a UAV group in executing tasks *** this paper,an attempt is made to perform a comprehensive review of the research on CPP for UAV ***,a generalized optimization framework of CPP problems is proposed from the viewpoint of three key elements,i.e.,task,UAV group,and environment,as a basis for a comprehensive classification of different types of CPP *** following the proposed framework,a taxonomy for the classification of existing CPP problems is proposed to describe different kinds of CPPs in a unified ***,a review and a statistical analysis are presented based on the taxonomy,emphasizing the coordinative elements in the existing CPP *** addition,a collection of challenging CPP problems are provided to highlight future research directions.

关键词： Unmanned aerial vehicle group Cooperation Path planning Optimization problem

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DR-WLC: Dimensionality Reduction cognition for object detection and pose estimation by Watching, Learning and Checking

arXiv

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arXiv 2023年

作者： Gao, Yu Xu, Xi Jiang, Tianji Chen, Siyuan Yang, Yi Yue, Yufeng Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Object detection and pose estimation are difficult tasks in robotics and autonomous driving. Existing object detection and pose estimation methods mostly adopt the same-dimensional data for training. For example, 2D object detection usually requires a large amount of 2D annotation data with high cost. Using high-dimensional information to supervise lower-dimensional tasks is a feasible way to reduce datasets size. In this work, the DR-WLC, a dimensionality reduction cognitive model, which can perform both object detection and pose estimation tasks at the same time is proposed. The model only requires 3D model of objects and unlabeled environment images (with or without objects) to finish the training. In addition, a bounding boxes generation strategy is also proposed to build the relationship between 3D model and 2D object detection task. Experiments show that our method can qualify the work without any manual annotations and it is easy to deploy for practical applications. Source code is at https: //***/IN2-ViAUn/DR-WLC. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

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Adaptive sliding mode control for Takagi-Sugeno fuzzy systems

Adaptive sliding mode control for Takagi-Sugeno fuzzy system...

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48th IEEE Conference on decision and control held jointly with 2009 28th Chinese control Conference, CDC/CCC 2009

作者： Zhang, Jinhui Shi, Peng Xia, Yuanqing Fu, Mengyin Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing 100081 China Faculty of Advanced Technology University of Glamorgan Pontypridd CF37 1DL United Kingdom School of Engineering and Science Victoria University Australia

ISBN: (纸本)9781424438716

This paper is devoted to robust adaptive sliding mode control for a class of nonlinear systems in the Takagi-Sugeno forms with mismatched parametric uncertainties. Sufficient conditions for the existence of linear sliding surfaces are given in terms of linear matrix inequalities, by which the corresponding adaptive reaching motion controller is also designed. Simulation studies show the effectiveness of the control scheme. ©2009 IEEE.

关键词： Linear matrix inequalities

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The Gait Planning Theory and Technology Research on the Wheel-foot Multi-joint Mobile Robot

The Gait Planning Theory and Technology Research on the Whee...

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第26届中国控制与决策会议

作者： Zhang Yeqing Luo Qingsheng Wang Meiling Wu Fan Wu Di Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Mechanic and Electronic Engineering Beijing Institute of Technology

Based on the excellent mechanical structure of the wheel-foot multi-joint mobile robot, we have strictly deduced the direct and inverse kinematical formulas of the robot's legs. So the theoretical method and technology of gaits control for the wheel-foot multi-joint mobile robot have been explored out. By precisely analyzing the obstacle performance and the workspace of the robot's feet, the constraints and efficiency of the robot have been illustrated clearly. After studying the features of various gaits, we also have designed four kinds of specific gaits for the wheel-foot multi-joint mobile robot, including the swing forward gait, the crab-lateral gait, the bent-knee forward gait and the wheel-turn gait, to verify the mobile ability and control effects of the robot. Then we research most fully on the control features, the attitudes of legs, the simulation effects and the fluctuation of the robot's body when walking with these four kinds of gaits, in order to fully understand the performance of the robot. The results of simulations and actual prototype tests have proved that the wheel-foot multi-joint mobile robot, with special mechanical structure and reasonable gaits planning, can move fast and steadily with versatile gaits in various complex terrains. The effectiveness of the theoretical exploration and the technical implementation has been fully proved in this paper.

关键词： mechanical structure kinematical formulas workspace of feet walking gaits prototype test

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