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检索条件"机构=the State Key Laboratory of Robotics and the Key Laboratory of Networked Control Systems"

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Link from ZD control to pascal's triangle illustrated via multiple-integrator systems

Link from ZD control to pascal's triangle illustrated via mu...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Yunong Zhang Huinan Xiao Dechao Chen Sitong Ding Pei Chen School of Information Science and Technology Sun Yat-sen University (SYSU) Guangzhou China Ministry of Education Key Laboratory of Autonomous Systems and Networked Control Guangzhou China SYSU-CMU Shunde International Joint Research Institute Foshan China

ISBN: (纸本)9781509040940

This paper researches the tracking-control problem of multiple-integrator (MI) systems via Zhang dynamics (ZD), which is a powerful class of dynamics to solve online time-varying problems. Based on design procedures of the so-called ZD controllers for five low-order integrator systems, the general formula of the ZD controller for the nth-order integrator system is elaborately given, and theoretical analyses are conducted to substantiate the excellent exponential convergence performance of the tracking controllers of the MI systems. In addition, the link from ZD control to Pascal's triangle (PT) found in this paper contributes to a quick and proper acquisition of the mathematical expression of the ZD controller.

关键词： Convergence Trajectory Fuzzy systems Knowledge discovery Information science Sun

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Fast, finite, accurate and optimal WASD neuronet versus slow, infinite, inaccurate and rough BP neuronet illustrated via russia population prediction

Fast, finite, accurate and optimal WASD neuronet versus slow...

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International Conference on Intelligent control and Information Processing (ICICIP)

作者： Jianxi Liu Yunong Zhang Zhengli Xiao Tianjian Qiao Hongzhou Tan Ministry of Education Key Laboratory of Autonoumous Systems and Networked Control Guangzhou China SYSU-CMU Shunde International Joint Research Institute Foshan China School of Information Science and Technology Sun Yat-sen University (SYSU) Guangzhou China

ISBN: (纸本)9781479917181

Russia population problem attracts great concerns to the future trend of population and the development of the nation. Conventional researches on Russia population prediction are usually based on the standard cohort-component method. Such a method only allows for several factors (fertility, mortality and migration rates), and then leads to the lack of all-sidedness in the prediction results. With outstanding generalization ability, the feedforward neuronet is considered to be a more appropriate substitute. Besides, the back-propagation (BP) is of the most widely-used feedforward neuronet. As the conventional back-propagation neuronet has some inherent weaknesses, in this paper, two types of improved feedforward neuronet are constructed for the Russia population prediction. More specifically, a type of 3-layer power-activated neuronet (PAN) equipped with the BP algorithm (BP-PAN) and a type of 3-layer PAN equipped with the weights-and-structure-determination (WASD) algorithm (WASD-PAN) are built on the basis of 2013-year (from 1AD to 2013AD) historical population data for the Russia population prediction. By a lot of numerical experiments, the future declining trend of Russia population in the next decade is predicted with the highest possibility. In addition, via the Russia population prediction, the comparisons on the performance between the WASD neuronet and BP neuronet are conducted and summarized.

关键词： Sociology Statistics Neurons Prediction algorithms Feedforward neural networks Data models Training

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Design of a Novel Autonomous Docking System With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

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Performance Improvement in Communication-Based Train control (CBTC) systems using Cognitive control

Performance Improvement in Communication-Based Train Control...

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IEEE International Conference on Intelligent Transportation systems

作者： Wenzhe Sun F. Richard Yu Tao Tang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University P.R. China Department of Systems and Computer Engineering Carleton University Ottawa ON Canada

Communication-Based Train control (CBTC) systems use bidirectional train-wayside wireless communications to ensure the safe operation of rail vehicles. Due to unreliable wireless networks, the uncertainties in train status information leads to imperfect traction/braking commands, which will affect CBTC performance. In this paper, we use recent advance in cognitive control to positively improve control performance as well as reduce information uncertainties. A cognitive control system composed of networked control System (NCS)-based state-space model and entropic-state model is presented. The performance optimization problem based on communication period decision and Medium Access control (MAC)-layer parameters adaption is formulated as a stochastic control process. Minimizing the energy consumption and information uncertainties is the objective of our model. Simulation result shows that the proposed cognitive control scheme can improve CBTC performance.

关键词： control systems Delays Uncertainty Adaptation models Wireless networks Rails state-space methods

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Composite Learning for Trajectory Tracking control of Robot Manipulators with Output Constraints

Composite Learning for Trajectory Tracking Control of Robot ...

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International Conference on Information Science and Technology (ICIST)

作者： Dianye Huang Chenguang Yang Yongping Pan Shilu Dai Zhaojie Ju Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Department of Biomedical Engineering National University of Singapore Singapore Singapore School of Computing University of Portsmouth Portsmouth UK

In this paper, a trajectory tracking scheme for robot manipulators with unknown dynamics is investigated, with the consideration of output constraints as well as small bounded external disturbances. Firstly, a modified backstepping control scheme is employed to control the robot manipulators where in the first step of the design a tan-type barrier Lyapunov candidate is chosen in order to tackle the constraint problem. Secondly, the philosophy of dynamic surface control is incorporated to implement the calculation of prediction errors, which can also reduce “explosion of complexity” of the backstepping scheme. In addition, composite learning is introduced for a better estimation of unknown parameters, and for canceling out the uncertainties of the robot manipulators. Stability analysis shows that the proposed control scheme guarantees a small bounded tracking error with parameter convergence in the absence of the stringent persistent excitation condition. Finally, a simulation is conducted and the results demonstrate the superiority of the proposed controller in the aspects of tracking capability and parameter estimation.

关键词： Manipulator dynamics Backstepping Uncertainty control systems Convergence

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Design and Implementation of a Group control Communication System for Intelligent Rubber Tapping Robots

Design and Implementation of a Group Control Communication S...

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第42届中国控制会议

作者： Fuchun Liu Dong Jiang Xiaoyang Chen Xujian Chen Shengfeng Huang School of Automation Science and Engineering South China University of Technology Key Laboratory of Autonomous Systems and Networked ControlMinistry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong Beijing Normal University Hong Kong Baptist United International College

With the development and promotion of electric rubber tapping equipment,China has gradually mechanized rubber tapping,but the degree of automation could be *** paper designs an intelligent rubber tapping remote monitoring system based on Internet of Things(IoT) technology that is applied to single-motor driven rubber tapping robots and uploads the status data of robots in the rubber plantation to the cloud database for storage,data analysis,and display in the backend management system in order to realize the intelligent and digital upgrade of rubber tapping *** can achieve remote group control of the robots in the rubber plantation at the same time using a cloud-based human-machine *** system consists of a terminal electronic control subsystem,a communication subsystem,and a cloud-based backend management *** system uses LoRa RF technology and Narrowband IoT(NBIoT) technology to design a star-shaped network to connect the robots to the cloud for unified management and provide data support for later tapping decisions.

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ZG tracking controller of z2g1 type for fractional power system

ZG tracking controller of z2g1 type for fractional power sys...

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International Conference on Information and Automation (ICIA)

作者： Yunong Zhang Fangzheng Lai Liangyu He Wan Li Jinjin Wang Ministry of Education Key Laboratory of Autonomous Systems and Networked Control Guangzhou China SYSU-CMU Shunde International Joint Research Institute Foshan China School of Data and Computer Science Sun Yat-sen University (SYSU) Guangzhou China

ISBN: (纸本)9781509041039

The output tracking control problem of fractional power system is investigated in this paper. By combining Zhang dynamics (ZD) method and gradient dynamics (GD) method, i.e., the so-called ZG method, a tracking controller of z2g1 type is proposed for fractional power system. The design procedure is illuminated through a specific fractional power system. Besides, the method can be extended to the more general high-order nonlinear system of fractional power. Finally, four examples are included to show the feasibility and effectiveness of ZG method.

关键词： Trajectory Power system stability Nonlinear dynamical systems Power system dynamics

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Optimal parameter value of Zhang equivalence for MVN redundancy resolution at velocity and acceleration levels

Optimal parameter value of Zhang equivalence for MVN redunda...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Yunong Zhang Xiaogang Yan Yinyan Zhang Dechao Chen Hongzhou Tan School of Information Science and Technology Sun Yat-sen University (SYSU) Guangzhou China Ministry of Education Key Laboratory of Autonomous Systems and Networked Control Guangzhou China SYSU-CMU Shunde International Joint Research Institute Foshan China

The equivalent relationship of two general scheme formulations at joint velocity and joint acceleration levels is established in this paper for robotic redundancy resolution, i.e., the so-called Zhang equivalence (ZE). As one representative case, ZE of the minimum velocity norm (MVN) type (i.e., MVN-type ZE) is further investigated for redundancy resolution. Moreover, computer simulations together with illustrative numerical experiments based on the widely-used robot manipulator PUMA560 show the phenomenon that an optimal equivalence value of the equivalent parameter exists within effective range from two different perspectives of equivalence; and then reveal the optimal value of the equivalent parameter in two situations from such perspectives.

关键词： Redundancy Manipulators Acceleration Kinematics Computer simulation Computers

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Identification of muscle morphology with noncontact capacitive sensing: Preliminary study

Identification of muscle morphology with noncontact capaciti...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Enhao Zheng Jiacheng Wan Dongfang Xu Qining Wang Hong Qiao The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Information Engineering China university of geosciences (Beijing) Beijing China The Robotics Research Group College of Engineering Peking University Beijing China

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Human-machine interface with muscle signals serves as an important role in the field of wearable robotics. To compensate for the limitations of the existing surface Electromyography (sEMG) based technologies, we previously proposed a noncontact capacitive sensing approach that could record the limb shape changes. The sensing approach frees the human skin from contacting to the metal electrodes, thus enabling the measurement of muscle signals by dressing the sensing front-ends outside of the clothes. We validated the capacitive sensing in human motion intent recognition tasks with the wearable robots and produced comparable results to existing studies. However, the biological significance of the capacitance signals is still unrevealed, which is an indispensable issue for robot intuitive control. In this study, we address the problems of identifying the relationships between the muscle morphological parameters and the capacitance signals. We constructed a measurement system that recorded the noncontact capacitive sensing signals and the muscle ultrasound (US) images simultaneously. With the designed device, five subjects were employed and the US images from the gastrocnemius muscle (GM) and the tibialis anterior (TA) muscle during level walking were sampled. We fitted the calculated muscle morphological parameters (the pinnation angles and the muscle fascicle length) and the capacitance signals of the same gait phases. The results demonstrated that at least one-channel capacitance signal strongly correlated to the muscle morphological parameters (R 2 > 0.5, quadratic regression). The average R 2 s of the most correlated channels were up to 0.86 for pinnation angles and 0.83 for the muscle fascicle length changes. The interesting findings in this preliminary study suggest the biological physical significance of the capacitance signals during human locomotion. Future efforts are worth being paid in this new research direction for more promising results.

关键词： Muscles Robot sensing systems Capacitance Legged locomotion Electrodes Ultrasonic variables measurement

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Residual Squeeze-and-Excitation Network with Multi-scale Spatial Pyramid Module for Fast Robotic Grasping Detection

Residual Squeeze-and-Excitation Network with Multi-scale Spa...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Hu Cao Guang Chen Zhijun Li Jianjie Lin Alois Knoll Chair of Robotics Artificial Intelligence and Real-Time Systems Technische Universität München München Germany State Key Laboratory of Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Tongji University Shanghai China University of Science and Technology of China China

This paper proposes an efficient, fully convolutional neural network to generate robotic grasps by using 300×300 depth images as input. Specifically, a residual squeeze-and-excitation network (RSEN) is introduced for deep feature extraction. Following the RSEN block, a multi-scale spatial pyramid module (MSSPM) is developed to obtain multi-scale contextual information. The outputs of each RSEN block and MSSPM are combined as inputs for hierarchical feature fusion. Then, the fused global features are upsampled to perform pixel-wise learning for grasping pose estimation. The experimental results on Cornell and Jacquard grasping datasets indicate that the proposed method has a fast inference speed of 5ms while achieving high grasp detection accuracy of 96.4% and 94.8% on Cornell and Jacquard, respectively, which strikes a balance between accuracy and running speed. Our method also gets a 90% physical grasp success rate with a UR5 robot arm.

关键词： Automation Conferences Pose estimation Grasping Manipulators Feature extraction Inference algorithms

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