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24th International Conference on Neural Information Processing (ICONIP)

作者： Liu, Xin Yang, Chenguang Wang, Min He, Wei South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China

ISBN: (纸本)9783319701363;9783319701356

Due to inevitable uncertainties associated with the dynamics and kinematics of flexible joint manipulators, accurate models would not be available for control design. Furthermore, practically we may face the problem that state variables required by the controller are not measurable. In this paper, we focus on the control system design using a neural network observer to solve the aforementioned unmeasurable problem. A state observer of a general multivariable nonlinear systems based on neural network is proposed. It can be applied to systems with unknown dynamic model. To test the effectiveness of the state observer we design a PD controller combining with the observer proposed for the flexible joint manipulator whose model is unknown. The stability of the controlled system is shown by Lyapunov method. To test and verify the effectiveness of the state controller simulation studies are performed.

关键词： State observer RBF Neural network Flexible joint manipulator system

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Modeling and Simulation of Hand based on OpenSim and Leap Motion

Modeling and Simulation of Hand based on OpenSim and Leap Mo...

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Chinese Automation Congress (CAC)

作者： Hu, Zedong Yang, Chenguang He, Wei Li, Zhijun He, Shunzhan South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou Guangdong Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China

ISBN: (纸本)9781538635247

In the modern industry, human-robot collaboration is becoming more and more important. With the quick development of the small production, the demand of flexibility is growing heavily. Gesture recognition is important for the collaborative work of humans and robots. In industrial applications, the performance of such systems affects the safety of human workers and their manufacturing efficiency. In this paper, we create a realistic human model in OpenSim, and use the Leap Motion to identify the action of a man's hand. Through the transmission of data measured by the Leap Motion, the model we have created in the OpenSim will correctly track the hand's movement, and make the corresponding motion. The experimental results show that the performance of this method is satisfactory. With the help of this method, we can simulate the precise movements of human hands in real time.

关键词： hand model simulation Leap Motion OpenSim real time

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Euler-precision formula ZD3NgyP-Z applied to discrete control simulation of agitation tank

Euler-precision formula ZD3NgyP-Z applied to discrete contro...

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2017 Chinese Automation Congress, CAC 2017

作者： Zhang, Yunong Zhang, Jianxin Ding, Yaqiong Gong, Huihui Li, Jian Guangzhou510006 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou510640 China SYSU-CMU Shunde International Joint Reseach Institute Foshan528300 China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou510006 China

ISBN: (纸本)9781538635247

In this paper, a new type of Euler-precision 3-node g-proportional (3NgP) formula is proposed and investigated in the general framework of Zhang discretization (ZD), which is named formula ZD3NgPZ with subtype Z corresponding to the second (as well as student) coauthor. By Taylor expansion, we prove that formula ZD3NgPZ approximating the fst-order derivative can achieve an error pattern of O(g). Numerical experiments of approximation are conducted to show the efficacy of the formula. In the meanwhile, formula ZD3NgPZ is used in the discrete control and simulation of agitation tank system. Finally, numerical experiments of discretization are conducted and analyzed to illustrate the efficacy and accuracy of formula ZD3NgPZ applied to agitation tank system. © 2017 IEEE.

关键词： Tanks (containers)

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Adaptive Compliance Learning control using Newton-Euler model 2

Adaptive Compliance Learning Control using Newton-Euler mode...

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2nd International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Liang, Congyuan Yang, Chenguang He, Wei Li, Zhijun South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing Peoples R China

ISBN: (纸本)9781538632604

In this article, an iterative learning control method using Newton-Euler model is proposed to apply in compliance interaction tasks. With the optimal impedance control model, the desired compliance performance would be able to be obtained. A learning impedance control law is investigated for estimating the system's unknown parameters. What's more, the control method proposed in this paper does not require the accurate measurement of the contact force. By applying Newton-Euler model to describe the manipulator model, the method will be more efficient. A rigorous analysis is also given in this paper. The validity of the proposed method is verified by simulations.

关键词： Impedance Manipulator dynamics Robot kinematics Force Mathematical model

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Neural control of Bimanual Robots With Guaranteed Global Stability and Motion Precision

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2017年第3期13卷 1162-1171页

作者： Yang, Chenguang Jiang, Yiming Li, Zhijun He, Wei Su, Chun-Yi South China Univ Technol Key Lab Autonomous Syst & Networked Control Minist Educ Guangzhou 510641 Guangdong Peoples R China Swansea Univ Zienkiewicz Ctr Computat Engn Swansea SA1 8EN W Glam Wales Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China

Robots with coordinated dual arms are able to perform more complicated tasks that a single manipulator could hardly achieve. However, more rigorous motion precision is required to guarantee effective cooperation between the dual arms, especially when they grasp a common object. In this case, the internal forces applied on the object must also be considered in addition to the external forces. Therefore, a prescribed tracking performance at both transient and steady states is first specified, and then, a controller is synthesized to rigorously guarantee the specified motion performance. In the presence of unknown dynamics of both the robot arms and the manipulated object, the neural network approximation technique is employed to compensate for uncertainties. In order to extend the semiglobal stability achieved by conventional neural control to global stability, a switching mechanism is integrated into the control design. Effectiveness of the proposed control design has been shown through experiments carried out on the Baxter Robot.

关键词： Bimanual robots global uniformly ultimately boundedness (GUUB) neural networks (NNs) tailored tracking performance

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Haptic Identification by ELM-controlled Uncertain Manipulator

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2017年第8期47卷 2398-2409页

作者： Yang, Chenguang Huang, Kunxia Cheng, Hong Li, Yanan Su, Chun-Yi South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China Univ Elect Sci & Technol China Ctr Robot Chengdu 611731 Sichuan Peoples R China Imperial Coll London Dept Bioengn London SW2 7AZ England

This paper presents an extreme learning machine (ELM)-based control scheme for uncertain robot manipulators to perform haptic identification. ELM is used to compensate for the unknown nonlinearity in the manipulator dynamics. The ELM enhanced controller ensures that the closed-loop controlled manipulator follows a specified reference model, in which the reference point as well as the feedforward force is adjusted after each trial for haptic identification of geometry and stiffness of an unknown object. A neural learning law is designed to ensure finite-time convergence of the neural weight learning, such that exact matching with the reference model can be achieved after the initial iteration. The usefulness of the proposed method is tested and demonstrated by extensive simulation studies.

关键词： Adaptive control extreme learning machine (ELM) haptic identification robot manipulator

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Euler-precision ZED formula 3NgPED-G extended to future minimization with theoretical guarantees and numerical experiments 2

Euler-precision ZED formula 3NgPED-G extended to future mini...

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2nd IEEE Advanced Information Technology, Electronic and Automation control Conference, IAEAC 2017

作者： Zhang, Yunong Gong, Huihui Li, Jian Huang, Huanchang Yang, Min School of Information Science and Technology Sun Yat-sen University Guangzhou510006 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou510640 China SYSU-CMU Shunde International Joint Reseach Institute Shunde528300 China

ISBN: (纸本)9781467389778

In this paper, we propose and investigate a new Euler-precision 3-node g-proportional finite difference formula [also named Zhang finite difference (ZFD) formula 3NgPFD-G], which achieves an error pattern of O(g), where g denotes the sampling gap. Moreover, the proposed formula is extended to future minimization (FM). Specifically, the ZFD formula 3NffPFD-G and its extension to discretize continuous-time Zhang neural network (CTZNN) model for solving FM are first of all put forward. Secondly, the ZFD formula 3NgPFD-G is proved to effectively approximate the 1st-order derivative by Taylor expansion, and results of discrete-time Zhang neural network (DTZNN) model for solving FM are obtained by adopting the formula above to discretize the CTZNN model. Finally, expository numerical approximation and discretization experiments are conducted and analyzed to illustrate the efficacy and superiority of the ZFD formula 3NgPFD-G and its extension to FM. © 2017 IEEE.

关键词： Neural network models

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Solving ordinary differential equations by ZED 4IgSFD-L method 36

Solving ordinary differential equations by ZED 4IgSFD-L meth...

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36th Chinese control Conference, CCC 2017

作者： Zhang, Yunong Yang, Xuyun Huang, Huanchang Li, Wan Lai, Fangzheng School of Information Science and Technology Sun Yat-sen University Guangzhou510006 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou510640 China SYSU-CMU Shunde International Joint Research Institute Foshan528300 China

ISBN: (纸本)9789881563934

Ordinary differential equations (ODEs) are commonly used in physical system and automation researches, describing the relationship among variables. Hence there are practical significances to discuss and to research the solutions of ODEs. The initial value problem (IVP) is one of the important parts, and we usually use traditional methods, e.g. Euler method, to obtain the solutions. In this paper, we propose a new method named ZFD (Zhang finite difference) 4IgSFD-L method. Note that this method is developed by using ZFD formula 4IgSFD-L (4-instant g-square finite difference with subtype L) based on Taylor expansion, with g denoting sampling gap and g 2). © 2017 Technical Committee on control Theory, CAA.

关键词： Taylor series Differential equations Electronic mail Layout autonomous systems Trajectory

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ZFD formula 4IgSFD_Y applied to future minimization

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PHYSICS LETTERS A 2017年第19期381卷 1677-1681页

作者： Zhang, Yunong Yang, Min Li, Jian He, Liu Wu, Sheng Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Foshan 528300 Peoples R China Minist Educ Key Lab Machine Intelligence & Adv Comp Guangzhou 510006 Guangdong Peoples R China

In this paper, a 4-instant g-square finite difference formula with subtype Y [termed Zhang finite difference (ZFD) formula 4IgSFD_Y] with analysis and application for future minimization (i.e., discrete time varying minimization) is proposed and investigated, where g denotes the sampling gap. At first, a continuous-time zeroing neural network (ZNN) model is presented for continuous -time varying minimization. The proposed ZFD formula 4IgSFD_Y effectively approximates the 1st-order derivative in computation, and a discrete -time ZNN model is obtained by adopting the ZFD formula 4IgSFD_Y to discretize the continuous-time ZNN model. For comparison, Newton iteration for the future minimization is also presented in this paper. In addition, the discrete-time ZNN model with 0 (g(3)) residual error pattern performs more accurately than the Newton iteration with 0 (g) residual error pattern. Finally, illustrative numerical experiments are conducted and analyzed to show the efficacy and superiority of the discrete -time ZNN model for the future minimization. (C) 2017 Elsevier B.V. All rights reserved.

关键词： 4-instant g-square finite difference Discrete-time Zeroing neural network (ZNN) Future minimization

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Application of Kalman Filtering Algorithm in Laser Triangulation Measurement

Application of Kalman Filtering Algorithm in Laser Triangula...

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第36届中国控制会议

作者： WEN Xiao-qin LIANG Jun-yuan Ministerial Key Laboratory of Autonomous Systems and Networked Control School of Automation Science and EngineeringSouth China University of Technology

In order to improve the measurement precision of the laser displacement ***,the cause of the error caused by the measured surface features is analyzed from the measurement principle of laser ***,according to the result of error analysis,the Kalman filter algorithm is applied to the sensor data to carry out error ***,the experiments were carried out with LS-100 CP laser displacement sensor and *** experimental results show that the Kalman filter algorithm in the application of laser triangula tion measurement is feasible,effective and have a good practical value.

关键词： Kalman filter algorithm triangulation method data processing measurement precision

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