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Constrained Multilegged Robot system Modeling and Fuzzy control With Uncertain Kinematics and Dynamics Incorporating Foot Force Optimization

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2016年第1期46卷 1-15页

作者： Li, Zhijun Xiao, Shengtao Ge, Shuzhi Sam Su, Hang S China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Network Control Guangzhou 510641 Guangdong Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore 117576 Singapore Univ Elect Sci & Technol China Ctr Robot Chengdu 610054 Peoples R China

This paper studies the optimal distribution of feet forces and control of multilegged robots with uncertainties in both kinematics and dynamics. First, a constrained dynamics for multilegged robots and the constrained environment model are established by considering both kinematic and dynamic uncertainties. Under an external wrench for multilegged robots, the foot forces and moments of the supporting legs can be formulated as quadratic programming problems subject to linear and nonlinear constraints. The neurodynamics of recurrent neural network is developed for foot force optimization. For the obtained optimized tip-point force and the motion of legs, we propose a hybrid task-space trajectory and force tracking based on fuzzy system and adaptive mechanism that are used to compensate for the external perturbation, kinematics, and dynamics uncertainties. The tracking of task-space trajectory and constraint force is achieved under unknown dynamical parameters, constraints, and disturbances. Extensive simulations have been provided to verify the effectiveness of the proposed scheme.

关键词： Forces distribution fuzzy-based motion/force control kinematics and dynamics uncertainties multilegged robot

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Development of A Biofeedback Enhanced Multimedia Game 28

Development of A Biofeedback Enhanced Multimedia Game

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28th Chinese control and Decision Conference

作者： Wu, Huaiwei Yang, Chenguang Wang, Ruowei Su, Chun-Yi South China Univ Technol Sch Automat Sci & Engn MOE Key Lab Autonomous Syst & Network Control Guangzhou 510641 Guangdong Peoples R China Swansea Univ Ctr Computat Engn Swansea W Glam Wales

ISBN: (纸本)9781467397148

As a frontier technology, biofeedback has been widely used for psychological treatment, control and many other human-computer interaction applications. In this paper, a multimedia game based on biofeedback technology is developed, including two main parts, the design of a brain computer interface (BCI) and the design of a multimedia game. In the BCI design part, eletroencephlogram (EEG) signals are collected and sent to a processing module for classification. All EEG signals will be classified into two categories: movement or relaxation. Subsequently these classified results will be sent to the game process to control the action of a virtual car in real time. In the second part, the design of a multimedia game via QTCreator is presented. We mainly use QTCreator's Graphics View Frame to develop the game. At last we will introduce how to combine MATlab, SCAN4.5 and QTCreator together to play the game with biofeedback.

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Neural network-Based control of networked Trilateral Teleoperation With Geometrically Unknown Constraints

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IEEE TRANSACTIONS ON CYBERNETICS 2016年第5期46卷 1051-1064页

作者： Li, Zhijun Xia, Yuanqing Wang, Dehong Zhai, Di-Hua Su, Chun-Yi Zhao, Xingang S China Univ Technol Minist Educ Key Lab Autonomous Syst & Network Control Guangzhou 510641 Guangdong Peoples R China S China Univ Technol Coll Automat Sci & Engn Guangzhou 510641 Guangdong Peoples R China Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang 110016 Peoples R China Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

Most studies on bilateral teleoperation assume known system kinematics and only consider dynamical uncertainties. However, many practical applications involve tasks with both kinematics and dynamics uncertainties. In this paper, trilateral teleoperation systems with dual-master-single-slave framework are investigated, where a single robotic manipulator constrained by an unknown geometrical environment is controlled by dual masters. The network delay in the teleoperation system is modeled as Markov chain-based stochastic delay, then asymmetric stochastic time-varying delays, kinematics and dynamics uncertainties are all considered in the force-motion control design. First, a unified dynamical model is introduced by incorporating unknown environmental constraints. Then, by exact identification of constraint Jacobian matrix, adaptive neural network approximation method is employed, and the motion/force synchronization with time delays are achieved without persistency of excitation condition. The neural networks and parameter adaptive mechanism are combined to deal with the system uncertainties and unknown kinematics. It is shown that the system is stable with the strict linear matrix inequality-based controllers. Finally, the extensive simulation experiment studies are provided to demonstrate the performance of the proposed approach.

关键词： Hybrid force-motion control kinematic uncertainty networked trilateral teleoperation neural networks

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Trajectory-Tracking control of Mobile Robot systems Incorporating Neural-Dynamic Optimized Model Predictive Approach

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2016年第6期46卷 740-749页

作者： Li, Zhijun Deng, Jun Lu, Renquan Xu, Yong Bai, Jianjun Su, Chun-Yi S China Univ Technol Key Lab Autonomous Syst & Network Control Coll Automat Sci & Engn Guangzhou 200240 Guangdong Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China Guangdong Key Lab IoT Informat Proc Guangzhou 510006 Guangdong Peoples R China Hangzhou Dianzi Univ Inst Informat & Control Hangzhou 310018 Peoples R China Concordia Univ Dept Mech & Ind Engn Montreal PQ H3G 1M8 Canada

Mobile robots tracking a reference trajectory are constrained by the motion limits of their actuators, which impose the requirement for high autonomy driving capabilities in robots. This paper presents a model predictive control (MPC) scheme incorporating neural-dynamic optimization to achieve trajectory tracking of nonholonomic mobile robots (NMRs). By using the derived tracking-error kinematics of nonholonomic robots, the proposed MPC approach is iteratively transformed as a constrained quadratic programming (QP) problem, and then a primal-dual neural network is used to solve this QP problem over a finite receding horizon. The applied neural-dynamic optimization can make the cost function of MPC converge to the exact optimal values of the formulated constrained QP. Compared with the existing fast MPC, which requires repeatedly calculating the Hessian matrix of the Langragian and then solves a quadratic program. The computation complexity reaches O(n(3)), while the proposed neural-dynamic optimization contains O(n(2)) operations. Finally, extensive experiments are provided to illustrate that the MPC scheme has an effective performance on a real mobile robot system.

关键词： Model predictive controls (MPCs) neural-dynamic optimization quadratic programming (QP) problem trajectory tracking

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Adaptive Neural network Based Variable Stiffness control of Uncertain Robotic systems Using Disturbance Observer

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2017年第3期64卷 2236-2245页

作者： Zhang, Longbin Li, Zhijun Yang, Chenguang South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Network Control Guangzhou 510641 Guangdong Peoples R China Swansea Univ Zienkiewicz Ctr Computat Engn Swansea SA1 8EN W Glam Wales Southwest Univ Sci & Technol Sichuan Peoples R China South China Univ Technol Coll Automat Sci & Engn Guangzhou Peoples R China Shanghai Jiao Tong Univ Shanghai Peoples R China Univ Electrocommun Dept Mech Engn & Intelligent Syst Tokyo Japan Natl Univ Singapore Dept Elect & Comp Engn Singapore 117548 Singapore Nanyang Technol Univ Singapore Singapore Shanghai Jiao Tong Univ Dept Automat Shanghai Peoples R China Northwestern Polytech Univ Xian Peoples R China Natl Univ Singapore Singapore 117548 Singapore

The variable stiffness actuator (VSA) has been equipped onmany new generations of robots because of its superior performance in terms of safety, robustness, and flexibility. However, the control of robots with joints driven by VSAs is challenging due to the inherited highly nonlinear dynamics. In this paper, a novel disturbance observer based adaptive neural network control is proposed for robotic systems with variable stiffness joints and subject to model uncertainties. By utilizing a high-dimensional integral Lyapunov function, adaptive neural network control is designed to compensate for the model uncertainties, and a disturbance observer is integrated to compensate for the nonlinear VSA dynamics, as well as the neural network approximation errors and external disturbance. The semiglobally uniformly ultimately boundness of the closed-loop control system has been theoretically established. Simulation and extensive experimental studies have also been presented to verify the effectiveness of the proposed approach.

关键词： Adaptive neural network disturbance observer high-dimensional integral Lyapunov variable stiffness actuator (VSA)

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Frequency domain modelling and control of fractional-order system for permanent magnet synchronous motor velocity servo system

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IET control THEORY AND APPLICATIONS 2016年第2期10卷 136-143页

作者： Yu, Wei Luo, Ying Chen, YangQuan Pi, YouGuo Guang Dong Univ Technol Dept Automat Guangzhou Guangdong Peoples R China S China Univ Technol Key Lab Autonomous Syst & Network Control Minist Educ Dept Automat Sci & Engn Guangzhou 510641 Guangdong Peoples R China Univ Calif Merced Sch Engn Mechatron Embedded Syst & Automat MESA Lab ME EECS SNRI UCSolar Merced CA 95343 USA

This study presents fractional-order system modelling and control for a permanent magnet synchronous motor (PMSM) velocity servo system. Fractional-order model of the PMSM velocity servo system is obtained theoretically for an improved modelling precision. To identify the parameters of the proposed fractional-order model, an enhancement of the classic Levy identification method with weights is applied. In a real-time PMSM velocity servo plant, the fractional-order model is identified according to the experimental tests using the presented algorithm. The fact that the fractional model is more accurate than traditional integer-order model is substantiated using by the mean square error performance index. Two H stabilising output feedback controllers are designed for velocity servo using a simple scheme according to the identified fractional-order model and the traditional integer order one, respectively. The experimental test performance using these two designed H controllers is compared to demonstrate the advantage of the proposed fractional-order model of the PMSM velocity system.

关键词： permanent magnet motors synchronous motors machine control frequency-domain analysis servomotors angular velocity control identification mean square error methods performance index H control feedback stability control system synthesis frequency domain modelling fractional-order system modelling permanent magnet synchronous motor real-time PMSM velocity servo plant classic Levy identification method integer-order model mean square error performance index MSE H stabilising output feedback controllers

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Dynamic Balance Optimization and control of Quadruped Robot systems With Flexible Joints

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2016年第10期46卷 1338-1351页

作者： Li, Zhijun Ge, Quanbo Ye, Wenjun Yuan, Peijiang South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Network Control Guangzhou 510061 Guangdong Peoples R China Hangzhou Dianzi Univ Inst Informat & Control Hangzhou 310018 Zhejiang Peoples R China Concordia Univ Dept Mech & Ind Engn Montreal PQ H3G 1M8 Canada Beihang Univ Inst Robot Beijing 100191 Peoples R China

This paper investigates dynamic balance optimization and control of quadruped robots with compliant/flexible joints under perturbing external forces. First, we formulate a constrained dynamic model of compliant/flexible joints for quadruped robots and a reduced-order dynamic model is developed considering the robot interaction with the environment through multiple contacts. A dynamic force distribution approach based on quadratic objective function is proposed for evaluating the optimal contact forces to cope with the external wrench, and fuzzy-based adaptive control of compliant/flexible joints for quadruped robots is proposed to suppress uncertainties in the dynamics of the robot and actuators. The dynamic surface control approaches and fuzzy learning algorithms are combined in the proposed framework. All the signals of the closed-loop system have proven to be uniformly ultimately bounded through Lyapunov synthesis. Simulation experiments were performed for a quadruped robot with compliant/flexible joints. The benefits of its tracking accuracy and robustness indicate that the proposed framework is promising for the robots with payload uncertainties and external disturbances.

关键词： Dynamic force distribution fuzzy approximation motion/force control quadruped robots

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Kinematics Modeling of Geomagic Touch X Haptic Device based on Adaptive Parameter Identification

Kinematics Modeling of Geomagic Touch X Haptic Device based ...

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

作者： Jiang, Yiming Yang, Chenguang Wang, Xingjian Su, Chun-Yi South China Univ Technol Sch Automat Sci & Engn Key Lab Autonomous Syst & Network Control Guangzhou Guangdong Peoples R China Swansea Univ Zienkiewicz Ctr Computat Engn Swansea W Glam Wales Concordia Univ Dept Mech & Ind Engn Montreal PQ Canada

ISBN: (纸本)9781467389594

The Geomagic Touch X haptic device made by SensAble Technologies has been widely used for various applications, e.g., video games, medical training, and telerobot operation. It provides feedback forces and thus greatly enhances their telepresence user experience together with virtual reality techniques. Motion commands sent from Touch X to a remote device are used for position control in teleoperation. Therefore, an accurate kinematic model of Touch X device is essential for precise motion control. In this paper, the Denavit-Hartenberg (DH) convention is first applied to construct a kinematics model with parameters to be identified. To facilitate online control, an adaptive finite time (FT) estimation algorithm is adopted to identify the unknown kinematic parameters, and it guarantees that accurate values of the DH parameters arc obtained with a finite time convergence rate. Meanwhile, a purposely designed coordinate transformation is applied to match the coordinate of kinematics model and Touch X device. Hardware-in -loop simulation studies have been performed to compare the real end-effector's position and data calculated from our proposed model. The comparison results have demonstrated the effectiveness of the adaptive estimation developed in this paper.

关键词： Geomagic Touch X kinematics DH parameters adaptive estimation

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Mechatronic Design of a Human Robot Coupling Interface for Teaching by Demonstration

Mechatronic Design of a Human Robot Coupling Interface for T...

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7th IFAC Symposium on Mechatronic systems (MECHATRONICS)

作者： Liang, Peidong Yang, Chenguang Wang, Ning Li, Zhijun Li, Ruifeng Harbin Inst Technol State Lab Robot Syst Harbin Peoples R China Swansea Univ Zienkiewicz Ctr Computat Engn Swansea W Glam Wales Univ Plymouth Ctr Robot & Neural Syst Plymouth Devon England S China Univ Technol MOE Key Lab Autonomous Syst & Network Control Coll Automat Sci & Engn Guangzhou 510640 Guangdong Peoples R China

In this paper, we have developed a mechatronic human-robot coupling interface for kinaesthetic guidance based human robot teaching interface, by integration of a 6-axis force sensor, a coupling mechanism and wearable electromyography (EMG) arrays. Our design aims to transfer human operators arm kinematics, force as well as human upper limb stiffness estimated from EMG signals to robot manipulators. Experiments have been carried out to test the teaching by demonstration performance of the coupling system in two scenarios: i) human teaching a robot for lifting up task;ii) human-robot skill transfer for one joint motion. Experimental results indicated that the coupling design nearly caused no disturbance to human upper limb stiffness estimation. Moreover, human arm kinematics and force/torque in task space can be transferred to the robot in a natural way with guaranteed safety. This coupling interface design can be easily extended to other robot platforms and has great potentials in application of human robot skill transfer. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： human robot coupling teaching by demonstration electromyography(EMG)

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Kinematics modeling of Geomagic Touch X haptic device based on adaptive parameter identification

Kinematics modeling of Geomagic Touch X haptic device based ...

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

作者： Yiming Jiang Chenguang Yang Xingjian Wang Chun-Yi Su Key Lab of Autonomous System and Network Control South China University of Technology Guangzhou China Centre for Computational Engineering Swansea University UK Department of Mechanical and Industrial Engineering Concordia University Montreal Canada

ISBN: (纸本)9781467389600

The Geomagic Touch X haptic device made by SensAble Technologies has been widely used for various applications, e.g., video games, medical training, and telerobot operation. It provides feedback forces and thus greatly enhances their telepresence user experience together with virtual reality techniques. Motion commands sent from Touch X to a remote device are used for position control in teleoperation. Therefore, an accurate kinematic model of Touch X device is essential for precise motion control. In this paper, the Denavit-Hartenberg (DH) convention is first applied to construct a kinematics model with parameters to be identified. To facilitate online control, an adaptive finite time (FT) estimation algorithm is adopted to identify the unknown kinematic parameters, and it guarantees that accurate values of the DH parameters are obtained with a finite time convergence rate. Meanwhile, a purposely designed coordinate transformation is applied to match the coordinate of kinematics model and Touch X device. Hardware-in-loop simulation studies have been performed to compare the real end-effector's position and data calculated from our proposed model. The comparison results have demonstrated the effectiveness of the adaptive estimation developed in this paper.

关键词： Kinematics DH-HEMTs Robot kinematics Haptic interfaces Parameter estimation Mathematical model

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