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Analysis of router algorithms of tactical UAV group Ad hoc network router

Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology 2010年第SUPPL. 1期30卷 161-164页

作者： Chen, Wen-Jie Dou, Li-Hua Li, Yu-Jin School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

In this paper an Ad hoc networks are established for the communication among unmanned air vehicle (UAV) group corporation. It is brought out that reference point group mobility model (RPGM) could simulate the behavior of UAV group to analyze the efficiency of router algorithms as to the movement of UAV node. The result shows that the Ad hoc networks can solve the communication problem of UAV group, and also find out that the ADOV algorithm has data large throughout and more adaptive to the variation of topology, the DSR has a lighter routing load. The efficiency of router algorithm also changes as to the node speed. As a result the routing algorithm should be chosen according to the different tactical mission of UAV group, and the designs of corporation method should consider the changing of network efficiency as to node moving speed.

关键词： Unmanned aerial vehicles (UAV)

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Direct identification for the continuous models of servo systems with friction nonlinearity

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Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology 2010年第SUPPL. 1期30卷 86-90页

作者： Gan, Ming-Gang Gong, Wei-Guang Zhang, Guo-Zhu Chen, Jie Cai, Tao School of Automation Beijing Institute of Technology Beijing 100081 China Education Ministry Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China

In order to describe precisely the dynamics and friction nonlinearity of servo systems, a novel direct identification method for nonlinear continuous model is proposed. The sampled input-output data and logic data corresponding to the velocity direction are chosen as the identification data. Through equivalent transformation, the unknown parameters are removed to the linear part of the model. Then the identification method based on state variable filter is utilized to determine the unknown parameters. Subsequently, the nonlinear continuous model of the servo system is obtained. The effectiveness of the proposed method is demonstrated by simulations and identification experiments on the two axis servo table. Both the simulations and experimental results show that, with the proposed method, the accurate nonlinear continuous model can be obtained even under sensor noises, which gives an accurate description of the system dynamics.

关键词： Servomechanisms

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Backlash neural network model for hysteresis nonlinearity

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Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology 2007年第SUPPL. 1期27卷 226-230页

作者： Liao, Xiao-Zhong Lu, Guo-Hui Liu, Xiang-Dong Department of Automatic Control School of Information Science and Technology Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China

A Backlash neural network model is proposed for the systems with hysteresis nonlinearity. In order to approximate the hysteresis nonlinearity, Backlash-type operators are used as one layer of the neural network. Then, the number of Backlash operators and neurons of hidden layer are gotten through simulation. Compared with the normal BP network, the results show the improvement validity of the proposed Backlash neural network model for describing the hysteresis nonlinearity.

关键词： Nonlinear network analysis

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New approach for constructing BDD from a complex fault tree

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Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology 2007年第SUPPL. 1期27卷 140-144页

作者： Zhu, Lin Chen, Jie Chen, Wen-Jie Department of Automatic Control School of Information Science and Technology Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China

A new conversion method for fault tree (FT) to binary decision diagram (BDD) was introduced. Firstly, FT was reduced and the reduction rule was proposed, share-node conception was introduced on the basis of FT decomposition, then the rules of connection of component BDD was proposed. Furthermore the route-based BDD reduction rule was proved, with which reduction can be done at the same time with BDD composition, and the route sequence and cut sets can be obtained, while computation and storage is greatly reduced during the process. Finally, the procedure of the transformation is presented. The affectivity effectiveness and practicability is thereby proved.

关键词： Fault tree analysis

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Algorithm of improved marriage in honey bees optimization and convergence analysis

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Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology 2007年第SUPPL. 1期27卷 80-84页

作者： Yang, Chen-Guang Cai, Tao Tu, Xu-Yan Department of Automatic Control School of Information Science and Technology Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China

One problem of marriage in honey bees optimization (MBO) is that its complex computation process will limit its applications. The paper proposed an improved marriage honey bees optimization (IMBO). By randomly initializing drones and restricting the condition of iteration, the calculation process becomes easier. The global convergence characteristic of IMBO is also proved based on the Markov chain theory. With different number of nodes, traveling salesman problem(TSP) is used to compare the IMBO with MBO and genetic algorithm(GA). Simulation results show that IMBO has better convergence performance.

关键词： Genetic algorithms

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Distributed Cooperative decision-Making of Cross-Domain Swarm

Distributed Cooperative Decision-Making of Cross-Domain Swar...

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Chinese Automation Congress (CAC)

作者： Xingyu Liu Cheng Yuwen Wangcheng Zhang Mingyang Sun Ding Jian Ziyang Zhen State Key Laboratory of Mechanics and Control for Aerospace Structures College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China CASIC Research Institute of Intelligent Decision Engineering Wuhan China UAV System Company Limited Aviation Industry Corporation of China Chengdu China

This paper investigates a cooperative decision-making problem of the cross-domain swarm system involving unmanned surface vehicles (USVs) and unmanned aerial vehicles (UAVs). Different from the distributed optimization of multi-agent systems, the cooperative decision-making problem considers the payoff functions that depend on the states of all agents. Each agent can only adjust its own state. To address the cooperative decision-making problem, a two-time scale system is constructed, where the fast model includes an average consensus for gradient estimation of the global function and the slow model incorporates a feedback control of all USVs and UAVs. By the Lyapunov analysis, the optimal solution is globally exponentially stable. Finally, a cooperative encirclement task is utilized to verify the effectiveness of the proposed algorithm.

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Variable structure controller based on extended state observer in gun turret system

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Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology 2009年第4期29卷 318-322页

作者： Chen, Jie Jin, Tian-Xu Bai, Yong-Qiang Department of Automatic Control School of Information and Science Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision of Ministry of Education Beijing Institute of Technology Beijing 100081 China

Considering the characteristics of the servo system, such as disturbance, nonlinearity and high inertia, variable structure controller (VSC) based on extended state observers (ESO) are designed for the aim of quick, stable and high-accuracy controlling processes. The disturbances and high-order factors are estimated and compensated using ESO. Dynamic compensation reduces the motion system to approximately a triple integrator which can be easily controlled using VSC. Because ESO provides a high-frequency path for the dynamic state not modelled, the chatter of VSC is reduced. Through tests in the gun turret system, it was shown that this controller is superior to the engineering PID and general VSC.

关键词： Variable structure control

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Jialiang Luo Shichao Chen Yisheng Lv Wenqiao Sun Fan Yang Ruijie Xu The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University Jinan China Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Hong Kong China

With the rapid development and widespread application of Inertial Measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update Technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field.

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Deep Domain Adaptation Regression for Force Calibration of Optical Tactile Sensors

arXiv

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arXiv 2024年

作者： Chen, Zhuo Ou, Ni Jiang, Jiaqi Luo, Shan Robot Perception Lab Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sensors and existing tactile sensors which may have incurred damage or aging. However, the conventional neural-network-based force calibration method necessitates a large volume of force-labeled tactile images to minimize force prediction errors, with the need for accurate Force/Torque measurement tools as well as a time-consuming data collection process. To address this challenge, we propose a novel deep domain-adaptation force calibration method, designed to transfer the force prediction ability from a calibrated optical tactile sensor to uncalibrated ones with various combinations of domain gaps, including marker presence, illumination condition, and elastomer modulus. Experimental results show the effectiveness of the proposed unsupervised force calibration method, with lowest force prediction errors of 0.102N (3.4% in full force range) for normal force, and 0.095N (6.3%) and 0.062N (4.1%) for shear forces along the x-axis and y-axis, respectively. This study presents a promising, general force calibration methodology for optical tactile sensors. Copyright © 2024, The Authors. All rights reserved.

关键词： Forecasting

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TransForce: Transferable Force Prediction for Vision-based Tactile Sensors with Sequential Image Translation

arXiv

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arXiv 2024年

作者： Chen, Zhuo Ou, Ni Zhang, Xuyang Luo, Shan The Robot Perception Lab Centre for Robotics Research Department of Engineering King's College London LondonWC2R 2LS United Kingdom The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Vision-based tactile sensors (VBTSs) provide high-resolution tactile images crucial for robot in-hand manipulation. However, force sensing in VBTSs is underutilized due to the costly and time-intensive process of acquiring paired tactile images and force labels. In this study, we introduce a transferable force prediction model, TransForce, designed to leverage collected image-force paired data for new sensors under varying illumination colors and marker patterns while improving the accuracy of predicted forces, especially in the shear direction. Our model effectively achieves translation of tactile images from the source domain to the target domain, ensuring that the generated tactile images reflect the illumination colors and marker patterns of the new sensors while accurately aligning the elastomer deformation observed in existing sensors, which is beneficial to force prediction of new sensors. As such, a recurrent force prediction model trained with generated sequential tactile images and existing force labels is employed to estimate higher-accuracy forces for new sensors with lowest average errors of 0.69N (5.8% in full work range) in x-axis, 0.70N (5.8%) in y-axis, and 1.11N (6.9%) in z-axis compared with models trained with single images. The experimental results also reveal that pure marker modality is more helpful than the RGB modality in improving the accuracy of force in the shear direction, while the RGB modality show better performance in the normal direction. Copyright © 2024, The Authors. All rights reserved.

关键词： RGB color model

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