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International Conference on Information and automation (ICIA)

作者： Yi Yang Zhili Wang Xinghe Li Mengyin Fu Beijing Institute of Technology Beijing China Nanjing University of Science and Technology Nanjing China School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509041039

Accurate terrain estimation is essential for unmanned ground vehicle (UGV) to achieve autonomous navigation. However, some existing approaches are difficult to reconstruct the 3D surface in real-time because of serious amount of computation. A method of environmental terrain estimation based on multi-scale radial basis function with a 3D lidar mounted on a moving vehicle was proposed in this paper. By combining kernel template with terrain grid map, the approach is applicable to the non-uniform density distribution of laser point cloud with the increasing detection range and improves the efficiency of calculation. What's more, the estimation of culverts and trees will be more accurate if treat the point cloud in separate layers for suspended obstacles problem. All terrain estimation approaches were verified with good performance in an interactive system, which is set up with Virtual Robot Experimentation Platform (VREP) and actual vehicle.

关键词： Three-dimensional displays Estimation Laser radar Kernel Lasers Surface reconstruction Real-time systems

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Electronic compass calibration based on Adaptive Differential Evolution Algorithm-Fourier Neural Network

Electronic compass calibration based on Adaptive Differentia...

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作者： Gong, Kun Deng, Fang Chen, Jie School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

ISBN: (纸本)9789881725592

Based on the comparison of several common methods of electronic compass error compensation, this paper presents a new error compensation method based on Adaptive Differential Evolution-Fourier Neural Networks (ADE-FNN) to improve the measurement accuracy of electronic compass. This method uses Fourier neural network to model electronic compass error, and adopts Adaptive Differential Evolution to optimize the weights of neural network, and get more exact error model to compensate measured values. The compensation object is the common electronic compass composed by two-dimensional magnetic resistance sensor. Compared with the compensation effect of Least-square method, BP neural network and Fourier neural networks, It proves that the mode of this method can realize the high precision in the sample space mapping and high non-linear approximation ability, and this method has faster convergence rate, can avoid falling into local minima, reduces the training error, and improves error compensation accuracy. This method decreases the error range from 3.4° ∼ 25.2° before compensation to -0.20° ∼ 0.72°, and the average of the absolute error is 0.30°. Repeatability tests also proved the compensation plan have a good consistency. © 2011 Chinese Assoc of Automati.

关键词： Error compensation

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Design of a High Speed 360-degree Panoramic Video Acquisition system Based on FPGA and USB 3.0

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IEEE Sensors Journal 2023年 1-1页

作者： Lyu, Congyi Peng, Jianqing Zhou, Weiguo Yang, Shanshan Liu, Yunhui Intelligent Robotics Institute Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Mechatronical Engineering Beijing Institute of Technology Beijing China

This paper presents a FPGA-based hardware architecture for capturing real-time panoramic images and the parallel implementation of an image stitching algorithm based on the scale-invariant feature transform (SIFT) features. First, the system transfers the images captured by five CMOS sensors to the designed FPGA board through the FMC adapter plate. Then, the system employs the FPGA-based parallel computing to extract the SIFT features and detect the best matching region and points for image registration. Finally, in order to obtain the panoramic image with smooth changes at the junctions, images of the adjacent images are fused. Using the designed FPGA platform makes it possible to extract the SIFT and stitch the images in real-time, which is not realized in most panoramic imaging systems. The panoramic system, developed using the Xilinx Zynq®-7000 all programmable SOC, can capture video of 5*640*480 images at the speed of 60 fps. To enable high-speed image transfer from the imaging system to the host computer, the USB3.0 interface with the transmission speed of 359MB/s has been developed. The real-time efficiency of the parallel system will be demonstrated by the simulations and experiments. IEEE

关键词： Real time systems

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Autonomous Navigation and Obstacle Avoidance for Mobile Robots in a Tax Environment 13

Autonomous Navigation and Obstacle Avoidance for Mobile Robo...

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13th IEEE International Conference on CYBER Technology in automation, control, and intelligent systems, CYBER 2023

作者： Yu, Lianyi Wu, Zhengxing Jiang, Yang Tan, Min Yu, Junzhi Institute of Automation Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Northeastern University Shenyang110000 China BIC-ESAT State Key Laboratory for Turbulence and Complex System College of Engineering Peking University Department of Mechanics and Engineering Science Beijing100871 China

ISBN: (纸本)9798350315196

This paper focuses on the navigation and obstacle avoidance problems of intelligent mobile robots in a tax environment. Through combining the improved jump point search (JPS) and dynamic window approach (DWA) algorithms, a fusion path planning method is proposed for the mobile robots in tax services. Specially, a bi-directional JPS algorithm with an adaptive heuristic function is provided to decrease the search complexity and improve search flexibility in the global path planning. Meanwhile, considering the features of the tax environment, several evaluation subfunctions are particularly designed to leverage the global information and optimize the local path planning. Finally, various simulations and experiments in a Turtlebot3 robot validate the feasibility and effectiveness of the proposed method. The obtained results provide valuable guidance for the autonomous navigation research of the tax service robots. © 2023 IEEE.

关键词： Taxation

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Non-fragile finite-time dissipative piecewise control for time-varying system with time-varying delay

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IET control Theory & Applications 2019年第3期13卷 321-332页

作者： Menghua Chen Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 People's Republic of China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 People's Republic of China

This study is concerned with the problem of non-fragile finite-time dissipative (FTD) control for time-varying system with delay. The delay is time varying and belongs to a given interval. Finite-time bounded (FTB) and FTD concepts are introduced to time-varying system with delay. First, new FTB conditions are derived for time-varying system with delay by using a piecewise Lyapunov functional combined with reciprocally convex approach. Second, FTD conditions are obtained to guarantee that the time-varying system with delay is not only FTB but also satisfies a dissipative performance index. Moreover, based on the FTD conditions, the non-fragile piecewise feedback controllers are designed in terms of linear matrix inequalities (LMIs). In addition, an LMI-based iterative algorithm is given to obtain the piecewise feedback non-fragile controller gains. Finally, numerical examples demonstrate the effectiveness of the proposed method.

关键词： linear matrix inequalities delays feedback iterative methods control system synthesis Lyapunov methods time-varying systems performance index finite-time dissipative control time-varying system nonfragile piecewise feedback controllers piecewise feedback nonfragile controller gains time-varying delay nonfragile finite-time dissipative piecewise control finite-time bounded piecewise Lyapunov functional reciprocally convex approach dissipative performance index linear matrix inequalities LMI-based iterative algorithm

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A Fast Averaging Synchronization Algorithm for Clock Oscillators in Nonlinear Dynamical Network with Arbitrary Time-delays

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Acta Automatica Sinica 2010年第6期36卷 873-880页

作者： Jie CHEN Miao YU Li-Hua DOU Ming-Gang GAN School of Automation Beijing Institute of Technology Beijing 100081 P.R.China Key Laboratory of Complex System Intelligent Control and Decision of the Ministry of Education Beijing Institute of Technology Beijing 100081 P. R. China

This paper investigates the synchronization problem of clock oscillators in nonlinear dynamical network with arbitrary time-delays. First, a dynamic synchronization algorithm based on consensus control strategy, named fast averaging synchronization algorithm (FASA), is presented to find a solution to the synchronization problem. This algorithm can compensate the clock skew and offset differences between clock nodes, achieving the synchronization of clock nodes in a shorter time as compared to previous synchronization methods. Second, because of the dynamical performance of FASA, it is characterized from the perspective of compartmental dynamical system with arbitrary time-delays. In this case, the algorithm guarantees the states of all clock nodes in dynamical network converge to Lyapunov stable equilibria. Finally, numerical simulations and experimental results demonstrate the correctness and efficiency of the FASA, which means that the clock nodes can reach global consensus, and the synchronization error can reach nanosecond order of magnitude.

关键词： Clock synchronization dynamical network arbitrary time-delays consensus algorithm

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Observer-based finite time H ∞ control of nonlinear discrete time-varying systems with an adaptive event-triggered Mechanism

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Journal of the Franklin Institute 2020年第16期357卷 11668-11689页

作者： Menghua Chen Hamid Reza Karimi Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 China Department of Mechanical Engineering Politecnico di Milano Milan 20156 Italy Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 China

The problem of finite time stability and synthesis is discussed for nonlinear discrete time-varying systems by using the T-S fuzzy model. To reduce the communication network resources, two adaptive event-triggered mechanisms (AETMs) are taken into consideration in sensor-to-observer (S/O) and observer-to-controller (O/C) channels. The thresholds of the AETMs are adjusted according to the estimation error rather than some fixed ones. Sufficient conditions for developing an observer-based time-varying control are obtained, which ensure the time-varying error system to be finite time stable and satisfy the H ∞ performance simultaneously. Moreover, using the singular value decomposition technique, recursive linear matrix inequalities conditions are obtained for computing the gains of the controller and observer. Finally, the superiority and applicability of the proposed method are demonstrated by examples.

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Artificial Neural Network Based Maximum Power Point Tracking for PV system

Artificial Neural Network Based Maximum Power Point Tracking...

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第三十八届中国控制会议

作者： Al-wesabi Ibrahim Min Ding Xiaoling Jin Xianzhong Dai Mohammad Abu Sarhan Muhammed Badeaa Shafik Hao Zhou School of Automation China University of Geoscience Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Energy Research Institute School of electrical engineering and automation Wuhan university

Nowadays PV systems is suffering from two main problems: high production cost and low efficiency especially under variable weather conditions. Therefore, to reduce such associated problems, PV systems are being connected with various optimization controllers such as maximum power point tracking. In this paper, an artificial neural network maximum power point method has been designed to be linked between a PV system and DC-DC buck converter, and each part of the system is fully explained. The whole system was modeled under MATLAB/Simulink environment, simulation results demonstrated the efficiency of the proposed method. The proposed method has been examined to track the maximum power point under different weather conditions which shows a rapid and accurate tracking of the maximum power point(MPP) of PV system. The whole system which consists of PV arrays, Buck converter, ANN tracker, and load has been modeled using MATLAB/Simulink environment. This Simulink model has been examined using different levels of temperature and irradiation and the output results of both P-V and I-V characteristics, output power, and the system efficiency clearly demonstrate the validation of the modeled system. This demonstration has been done by comparing between the result of experimental platform and the results of simulated model which approves that ANN is highly recommended to be used in the field of maximum power point tracking of PV system.

关键词： Artificial neural network(ANN) Photovoltaic(PV) Maximum power point tracking(MPPT) Buck converter

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High-Precision Admittance control of Mechanical Arm Based on Force Sensor Compensation

High-Precision Admittance Control of Mechanical Arm Based on...

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第34届中国控制与决策会议

作者： Yaohui Wu Jiangbo Zhao Junzheng Wang Xin Zhang Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of Technology Technical center Xinxing Cathay International Group Co.Ltd.

Admittance control is one of the important methods of compliance *** is performed by inputting force signals and outputting position *** control can achieve high accuracy,but the force signals have large errors,which is an important factor affecting its *** the force sensor collects force data,there are non-negligible initial deviations due to gravity,installation,and other factors,resulting in poor admittance control *** order to solve this problem,this paper takes the six-degree-of-freedom manipulator admittance control as the research *** to the mapping relationship between the end attitude and the sensor errors,we propose a method of obtaining the initial offset value of the sensor through data *** method traverses the initial values of the sensor in each working posture when the sensor has no external force input,and then performs secondary interpolation to obtain the offset values of the sensor in any posture,corrects the output values of the force/torque sensor,and then improve the accuracy of admittance *** experimental results show that this method can quickly and effectively improve the calculation accuracy of the sensor's initial deviation values and the admittance control accuracy.

关键词： Admittance control Force/torque sensor Quadratic interpolation Precision optimization

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The Modeling and Estimation of Asynchronous Multirate Multisensor Dynamic systems

The Modeling and Estimation of Asynchronous Multirate Multis...

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第三十二届中国控制会议

作者： Liping Yan Bo Xiao Yuanqing Xia Mengyin Fu School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781479900305

This paper is concerned with the state estimation of a linear dynamic system and the fusion of asynchronous multirate multisensor *** dynamic system is described at the finest scale with multiple sensors observing a single target independently at different scales with different sampling *** main result is that the multiscale measurements are properly formulated,and an optimal recursive fusion algorithm is presented.A numerical example is given to show the feasibility and efficiency of the algorithm.

关键词： state estimation recursive fusion asynchronous multirate multiscale Kalman filter

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