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Implementation of Autonomous Docking and Charging for a Supporting Robotic Fish

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第7期70卷 7023-7031页

作者： Dong, Huijie Wu, Zhengxing Wang, Jian Chen, Di Tan, Min Yu, Junzhi Taiyuan Univ Technol Key Lab Adv Transducers & Intelligent Control Sys Minist Educ Taiyuan 030024 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Peking Univ Coll Engn Dept Adv Mfg & Robot State Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China Guangdong Ocean Univ Coll Elect & Informat Engn Zhanjiang 524088 Peoples R China

Underwater energy supplements for autonom- ous underwater vehicles (AUVs) are significant for ocean exploitation owing to energy storage and data communication limitations. Aiming at the energy supplement for bionic robotic fish, an autonomous recharging-oriented docking approach is proposed in this article. First, an omnidirectional docking system containing a supporting robotic fish capable of visual recognition and wireless charging and a docking platform is presented. Next, five locomotive modes are designed and analyzed based on the hybrid swimming and gliding patterns for the robot fish. Utilizing the five modes, a docking procedure is planned, and an onboard-visual-based autonomous docking control strategy is presented. Aquatic experiments, including docking with the platform and refloating a small robot, are performed to verify the effectiveness of the proposed approach. The obtained results offer valuable insights into the development of autonomous docking of bionic robots, laying a solid foundation for the permanent operation of various underwater devices and robots.

关键词： Robots Visualization Tail Shape Batteries Cameras Buoyancy Autonomous docking gliding robotic fish motion control underwater energy supplementation underwater robotics

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An overall solution of Virtual Reality Classroom

An overall solution of Virtual Reality Classroom

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IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)

作者： Dong, Xisong Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Qingdao Acad Intelligent Ind Inst Smart Educ Syst Qingdao Peoples R China

ISBN: (纸本)9781509029273

Virtual Reality (VR) is a three-dimensional computer-generated virtual world. It is essential to introduced VR technology to education area to develop new teaching mode to improve the efficiency and quality of teaching and learning. Among them, VR classroom has quickly become most dazzling star with its subversive advantage. This paper proposes an overall integration solution of VR classroom, including its composition, its scene design of various disciplines and its main advantage. Finally, a case study of a geography lesson is provided to show its advantages and strong potentiality.

关键词： Virtual Reality Education virtual classroom

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Traffic Flow Prediction with Parallel Data 21

Traffic Flow Prediction with Parallel Data

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21st IEEE International Conference on intelligent Transportation systems (ITSC)

作者： Chen, Yuanyuan Lv, Yisheng Wang, Xiao Wang, Fei-Yue Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao Qingdao 266109 Shandong Peoples R China

ISBN: (纸本)9781728103235

Traffic prediction is an elemental function of intelligent Transportation systems, and accurate and timely prediction is of great significance to both traffic management agencies and individual drivers. With the development of deep learning and big data, deep neural networks (DNN) achieve superior performances in traffic prediction. Developing DNN prediction models needs large scale and diverse data, however, it is costly to collect large volume of accurate traffic data. In this paper, we propose to use small volume of real traffic data and large volume of synthetic traffic data to developing traffic prediction models. The evolving of parallel system paradigm for traffic prediction and the algorithm to incrementally train traffic data generation models and traffic prediction models are presented. We use an improved generative adversarial networks to generate traffic data, and a stacked long short-term memory model for traffic prediction. Experimental results on a real traffic dataset demonstrate that our method can significantly improve the performance of traffic flow prediction.

关键词： Data models Predictive models Generators Gallium nitride Logic gates Transportation Computer architecture

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Development of the control System and Communication Network for intelligent SF6 High Voltage Circuit-Breaker

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Procedia Engineering 2012年 29卷 1690-1696页

作者： Qingchang Hao Guodong Yang Degang Yang En Li Zize Liang Dezheng Zhao State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences BeiJing 100190 China

This paper analyses the cause of the major faults of the SF6 high voltage circuit breaker, and then introduces a solution using an embedded control system. The control system consists of the controller for every breaker and a supervisor control system in the control center. Then a double-annular fiber field-bus communication network for the control system is introduced, of which the data link layer is implemented by the CAN controller. According to the operation state of every node and the fiber, the fiber communication module of every node can be configured to several different transmission modes. Due to the influence of temperature, the empirical formula of Beattie-Bridgman is used to calculate the pressure of SF6.

关键词： circuit breaker fiber communication CAN SF6 Beattie-Bridgman

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Fitting a functional structural plant model based on global sensitivity analysis

Fitting a functional structural plant model based on global ...

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2012 IEEE International Conference on Automation Science and Engineering: Green Automation Toward a Sustainable Society, CASE 2012

作者： Lin, Yubin Kang, Mengzhen Hua, Jing National Key Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781467304283

Calibration of a functional structural plant model is a challenging task because of the complexity of model structure. Parameter estimation through gradient-based optimization technique was highly dependent on initial parameter values. This motivated the use of global sensitivity analysis technique to choose parameter subset in fitting the data sequence. Global sensitivity indices were computed using the source sink ratio as the output of interest, which regulates all organ growth. By fitting on chrysanthemum data from nine sampling dates, it is shown that sensitivity analysis method helps to identify the influential parameters for a given sampling date. As a result, fitting process is less dependent on the initial parameter values. Current work provides a new method of calibrating a plant growth model with multiple outputs. © 2012 IEEE.

关键词： Sensitivity analysis

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Development of a Novel Robotic Dolphin and Its Application to Water Quality Monitoring

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2017年第5期22卷 2130-2140页

作者： Wu, Zhengxing Liu, Jincun Yu, Junzhi Fang, Hao Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Beijing Inst Technol Beijing Adv Innovat Ctr Intelligent Robots & Syst Beijing 100081 Peoples R China

This paper presents the mechatronic design and hydrodynamic analysis of a novel bioinspired robotic dolphin used formobile water qualitymonitoring. A complementary configuration for mimicry of dolphin-like propulsion is first presented, involving a waist-fluke propulsive unit for dorsoventral oscillations and a pair of flippers with separate degree of freedom for three-dimensional (3-D) maneuvers. A host of onboard sensors is equipped to strengthen the capability of environment perception and mission execution on a near real-time basis. Considering the dynamic requirement formotion transition in water quality monitoring, a central pattern generator based controller is then built to govern the multimodal locomotion of the robotic dolphin. Moreover, a 3-D dynamic model based on the Lagrange method is employed to predict the propulsive performance, followed by simulations of continuous diving and surfacing motions. Finally, both lab.ratory and field experiments are conducted to demonstrate the effectiveness of the presented mechatronic design and control methods. The results further show that the robotic dolphin with 3-D maneuverability offers a feasible solution to aquatic mobile sensing.

关键词： Bioinspired mobile sensing motion control robotic dolphin water quality monitoring

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Scanning the Issue and Beyond: Merton's Laws and Mertionian systems for ITS

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IEEE TRANSACTIONS ON intelligent TRANSPORTATION systems 2015年第6期16卷 2962 - 2969页

作者： Wang, Fei-Yue Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Natl Univ Def Technol Res Ctr Computat Expt & Parallel Syst Tech Changsha 410073 Hunan Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China

Presents a summary of the articles presented in this issue of the publication.

关键词： intelligent systems

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Enhancing Representation Power of Deep Neural Networks With Negligible Parameter Growth for Industrial Applications

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2024年第11期54卷 6837-6848页

作者： Chen, Liangming Jin, Long Shang, Mingsheng Wang, Fei-Yue Chinese Acad Sci Chongqing Key Lab Big Data & Intelligent Comp Chongqing Inst Green & Intelligent Technol Chongqing 400714 Peoples R China Univ Chinese Acad Sci Chongqing Sch Chongqing 400714 Peoples R China Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

In industrial applications where computational resources are finite and data noises are prevalent, the representation power of deep neural networks (DNNs) is crucial. Traditional network structures often require a significant increase in the parameter amount to enhance the representation power, making it difficult to achieve effective representation under parameter amount constraints. In order to alleviate this problem, this work leverages the ordinary differential equation (ODE) interpretation of deep residual networks, elucidating the relationship between the fine-grained connectivity modes of blocks in DNNs and the representation power. We build a bridge from the order of numerical methods and the order of ODEs to the representation power of DNNs. Besides, we show that higher-order ODEs can be approximated by k-step methods incorporating trainable coefficients. Empirically, we validate our theoretical insights by demonstrating the superior representation power of our proposed network structures through enhanced performance on industrial tasks, such as surface defect detection, critical temperature prediction of superconductors, and image classification under noises. The proposed method provides a new approach to the design of network structures for robust and accurate DNNs, enhancing the representation power with a negligible number of additional parameters. The code is publicly availab.e at https://***/LongJin-lab.Order-and-Representation-Power.

关键词： Residual neural networks Vectors Noise Biological neural networks Medical services Defect detection Agriculture Deep neural networks (DNNs) industrial applications ordinary differential equation (ODE) representation power

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Depth control of a Bioinspired Robotic Dolphin Based on Sliding-Mode Fuzzy control Method

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2018年第3期65卷 2429-2438页

作者： Yu, Junzhi Liu, Jincun Wu, Zhengxing Fang, Hao Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Beijing Inst Technol Beijing Adv Innovat Ctr Intelligent Robots & Syst Beijing 100081 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

This paper presents a hybrid controller that combines sliding-mode control (SMC) with a fuzzy strategy to regulate the vertical displacement of a bioinspired robotic dolphin. The structure of the robot and a simplified mathematical model for depth control are described. An SMC based on the line-of-sight guidance law and the slidingmode observer is developed to overcome systematic uncertainties and environmental disturbances. The Lyapunov stability theory is utilized to analyze the stability and convergence properties of the closed-loop system. Depth control in the physical robot is realized by utilizing a fuzzy logic controller, which is represented as the mapping of the input propulsion forces/ moments and output control parameters. Numerical and experimental results show that the proposed control strategy successfully steers the robot toward and along the desired depth.

关键词： Bioinspired robotic dolphin depth control fuzzy logic sliding-mode control (SMC)

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Electromagnetic Angular Position Sensing Using High-Magnetic-Permeability Materials

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IEEE SENSORS JOURNAL 2022年第12期22卷 11626-11636页

作者： Wang, Heng Wang, Shuangyi Rajamani, Rajesh South China Univ Technol Shien Ming Wu Sch Intelligent Engn Guangzhou 511442 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Minnesota Dept Mech Engn Minneapolis MN 55455 USA

In this paper, a new electromagnetic angular position sensing method using high-magnetic-permeability metal (e.g., mu-metal) is proposed for measurement of joint angles of rotational mechanisms. An electromagnet and magnetic sensors are both located on one mechanical part and the mu-metal element is located on the other mechanical part with relative rotation to the first part around the joint. The mu-metal with high magnetic permeability is easily magnetized by the electromagnet and it exerts an additional magnetic field on the magnetic sensors dependent on the rotation angle nonlinearly. This influence is utilized for angle estimation using an extended Kalman filter. Two configurations of the angle sensing system are designed and modeled using numerical simulation. Experimental results show that the angle measurement error for both configurations is under 1% over their respective sensing range. The mu-metal based angle sensing system is also validated to be immune to ferromagnetic disturbances due to the use of an alternating magnetic field. The proposed angle sensing method is non-contacting and non-intrusive, and its off-joint configuration can measure joint angle without needing to be installed in the joint.

关键词： Sensors Magnetic sensors Robot sensing systems Magnetic field measurement Electromagnets Estimation Magnetic separation Angular position sensing position estimation high-magnetic-permeabilitymaterial disturbance rejection

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