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International Conference on Unmanned systems and Artificial Intelligence

作者： Puyong Xu Chenguang Yang Shi-Lu Dai Zhaoyong Mao Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Unmanned System Research Institute Northwestern Polytechnical University Xi'an China

ISBN: (数字)9781728158594

ISBN: (纸本)9781728158600

In this paper, by focusing on trajectory tracking control of unmanned surface vessel (USV), we present a control method considering uncertain dynamics and output error constrains. Firstly, by using the properties of tan-type barrier Lyapunov function (BLF), the output tracking error can be constrained. Secondly, we use radical basis function neural network (RBF NN) to approximate the uncertain dynamics. Considering that the estimated parameters convergence cannot be achieved in the absence of persistent excitation (PE) conditions, the composite learning update law of the weight matrix in the NN is adopted to guarantee the parameters convergence under interval excitation (IE) conditions which is easier to reach. In simulation studies, it is proven that the USV have good ability to follow the pre-designed trajectory with small tracking error and the parameters convergence can be ensured.

关键词： unmanned surface vessel (USV) barrier Lyapunov function neural network composite learning Unmanned Surface Vessel Neural network outlet error network control control Methods neural network control follow error Converge Learning

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Finite-Time Convergence Adaptive Fuzzy control for Dual-Arm Robot With Unknown Kinematics and Dynamics

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IEEE TRANSACTIONS ON FUZZY systems 2019年第3期27卷 574-588页

作者： Yang, Chenguang Jiang, Yiming Na, Jing Li, Zhijun Cheng, Long Su, Chun-Yi South China Univ Technol Key Lab Autonomous Syst & Networked Control Coll Automat Sci & Engn Guangzhou 510640 Guangdong Peoples R China Kunming Univ Sci & Technol Fac Mech & Elect Engn Kunming 650500 Yunnan Peoples R China Univ Sci & Technol China Dept Automat Hefei 230026 Anhui Peoples R China Chinese Acad Sci Key Lab Complex Syst & Intelligence Sci Inst Automat Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China

Due to strongly coupled nonlinearities of the grasped dual-arm robot and the internal forces generated by grasped objects, the dual-arm robot control with uncertain kinematics and dynamics raises a challenging problem. In this paper, an adaptive fuzzy control scheme is developed for a dual-arm robot, where an approximate Jacobian matrix is applied to address the uncertain kinematic control, while a decentralized fuzzy logic controller is constructed to compensate for uncertain dynamics of the robotic arms and the manipulated object. Also, a novel finite-time convergence parameter adaptation technique is developed for the estimation of kinematic parameters and fuzzy logic weights, such that the estimation can be guaranteed to converge to small neighborhoods around their ideal values in a finite time. Moreover, a partial persistent excitation property of the Gaussian-membership-based fuzzy basis function was established to relax the conventional persistent excitation condition. This enables a designer to reuse these learned weight values in the future without relearning. Extensive simulation studies have been carried out using a dual-arm robot to illustrate the effectiveness of the proposed approach.

关键词： Dual-arm robots finite-time (FT) convergence fuzzy logic system (FLS) uncertain kinematics

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Broad Fuzzy Neural control Using Impedance Learning 4

Broad Fuzzy Neural Control Using Impedance Learning

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4th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Huang, Haohui Yang, Chenguang Ju, Zhaojie Yuan, Yuxia Li, Zhijun South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Peoples R China Univ West England Bristol Robot Lab Bristol BS16 1QY Avon England Univ Portsmouth Sch Comp Portsmouth PO1 3HE Hants England Univ Sci & Technol China Dept Automat Hefei 230026 Peoples R China

ISBN: (纸本)9781728100647

This work proposes a novel control strategy based on broad fuzzy neural network (BENN) by using impedance learning, which is subjected to contact with the unknown dynamic environment. Compared with the original fuzzy neural network, this framework is provided the prominent feature by taking the advantage of broad learning system (BLS) to approximate the unknown dynamic model. Aiming at offering a compliance contact scheme, this paper introduce the impedance learning to establish the robot-environment interaction model. Also, a stable controller, which is able to tackle the problems related to the state constrain, is designed through Barrier Lyapunov Function (BLF). The proposed method can achieve the favourable tracking action while guaranteeing the stability of closed-loop system. In the end, simulation study is performed to verify the effectiveness of BFNN with a two-DOF manipulator.

关键词： Impedance Fuzzy neural networks Manipulators Adaptation models Fuzzy control Force

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Position control of Continuum Manipulator with Twin-Pivot Compliant Joints

Position Control of Continuum Manipulator with Twin-Pivot Co...

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International Conference on Modelling, Identification and control (ICMIC)

作者： Xin Liu Chenguang Yang Shilu Dai Ying Feng Key Lab of Autonomous Systems and Networked Control South China University of Technology Guangzhou China

This paper proposes a novel closed-loop PD controller based on kinematic for continuum manipulator with twin-pivot compliant joints. The purpose of the twin-pivot compliant joints is to decrease the twisting angle caused by gravity of manipulator and payload. We build the forward and inverse kinematic to control the end-effector of continuum manipulator with twin-pivot compliant joints. In this paper, first we build forward and inverse kinematic of continuum manipulator with twin-pivot compliant joints. We then build the controller based on kinematic models for a continuum manipulator with 24 Degrees of Freedom (DoF). Finally, simulation studies are carried out to test the proposed approach.

关键词： Kinematics End effectors Jacobian matrices Service robots Aerospace electronics

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Exponential input-to-state stability of impulsive stochastic fuzzy Cohen-Grossberg neural networks with distributed infinite transmission delays

Exponential input-to-state stability of impulsive stochastic...

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第三十八届中国控制会议

作者： Weisong Zhou Dan Shi Wei Zhu Key Lab of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications

In this paper, we study a class of impulsive stochastic fuzzy delayed Cohen-Grossberg neural networks with distributed infinite transmission delays. By Razumikhin technique and differential inequalities, some sufficient conditions ensuring the mean-square exponential input-to-state stability of our considered Cohen-Grossberg neural networks are obtained. These results can include constant delay and bounded distributed delay as its special cases, and generalize and improve some earlier publications. A numerical example is demonstrated to verify the theoretical results.

关键词： Impulsive Stochastic Infinite delays Cohen-Grossberg neural networks Exponential input-to-state stability

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Interface Design of a Physical Human-Robot Interaction System for Human Impedance Adaptive Skill Transfer

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2018年第1期15卷 329-340页

作者： Yang, Chenguang Zeng, Chao Liang, Peidong Li, Zhijun Li, Ruifeng Su, Chun-Yi South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China Harbin Inst Technol State Key Lab Robot Syst Harbin 150001 Heilongjiang Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China

It has been established that the transfer of human adaptive impedance is of great significance for physical human-robot interaction (pHRI). By processing the electromyography (EMG) signals collected from human muscles, the limb impedance could be extracted and transferred to robots. The existing impedance transfer interfaces rely only on visual feedback and, thus, may be insufficient for skill transfer in a sophisticated environment. In this paper, physical haptic feedback mechanism is introduced to result in muscle activity that would generate EMG signals in a natural manner, in order to achieve intuitive human impedance transfer through a designed coupling interface. Relevant processing methods are integrated into the system, including the spectral collaborative representation-based classifications method used for hand motion recognition;fast smooth envelop and dimensionality reduction algorithm for arm endpoint stiffness estimation. The tutor's arm endpoint motion trajectory is directly transferred to the robot by the designed coupling module without the restriction of hands. Haptic feedback is provided to the human tutor according to skill learning performance to enhance the teaching experience. The interface has been experimentally tested by a plugging-in task and a cutting task. Compared with the existing interfaces, the developed one has shown a better performance. Note to Practitioners-This paper is motivated by the limited performance of skill transfer in the existing human-robot interfaces. Conventional robots perform tasks independently without interaction with humans. However, the new generation of robots with the characteristics, such as flexibility and compliance, become more involved in interacting with humans. Thus, advanced human robot interfaces are required to enable robots to learn human manipulation skills. In this paper, we propose a novel interface for human impedance adaptive skill transfer in a natural and intuitive manner. The developed int

关键词： Haptic feedback human impedance adaptive skill transfer physical human-robot interaction (pHRI) stiffness estimation

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Analysis of autonomous Vehicle Platoon with Disturbance Based on PLEXE

Analysis of Autonomous Vehicle Platoon with Disturbance Base...

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Chinese Automation Congress (CAC)

作者： Fuchun Liu Yonghao Long Hongbo Zhou School of Automation Science & Engineering The Key Laboratory of Autonomous Systems and Networked Control(ASNC) Ministry of Education South China University of Technology Guangzhou China School of Mechanical Engineering Hunan Institute of Science and Technology Yueyang China

The automation and coordination of vehicle has provided novel development opportunities for both the improvement of traffic efficiency and the efficiency and safety of vehicles within the platoon so that the research of related technology had becoming more and more popular. In this paper, we evaluate five traditional vehicle platoon auto-driving control algorithms in the sinusoidal scenario with disturbance. The simulation is realized in the PLEXE, which is an extension of the widespread vehicle network simulator Veins that allows the visually realistic simulation of platooning systems(i.e., automated car-following) and the analysis of mixed scenarios. For disturbance model in sinusoidal scenario, Gaussian noise is leveraged, which is a common disturbance of all kinds of system. Simulations' results indicate that, when the leader in the platoon driving with sinusoidal velocity with disturbance, Flatbed algorithm proposed by A. Ali, G. Garcia, and P. Martinet has higher stability and Anti-interference ability than the other four control algorithms. In addition, even under violent interference, this control law can maintain string stability (significant for platoon automation)and consistency of the platoon operations, such as consistent velocity and constant inter-vehicle gaps.

关键词： Automobiles Acceleration Stability analysis autonomous vehicles Cruise control Safety

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Robot Teleoperation System Based on Mixed Reality 4

Robot Teleoperation System Based on Mixed Reality

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4th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Liang, Congyuan Liu, Chao Liu, Xiaofeng Cheng, Long Yang, Chenguang South China Univ Technol Sch Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Peoples R China Univ Montpellier CNRS Dept Robot LIRMMUMR5506 161 Rue Ada F-34095 Montpellier France Changzhou Key Lab Robot & Intelligent Technol Changzhou 213022 Peoples R China Hohai Univ Jiangsu Key Lab Special Robots Changzhou 213022 Peoples R China Hohai Univ Coll IoT Engn Changzhou 213022 Peoples R China Chinese Acad Sci Inst Automat Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Univ West England Bristol Robot Lab Bristol BS16 1QY Avon England

ISBN: (纸本)9781728100647

This work develops a novel robot teleoperation system based on mixed reality. Combined with Leap Motion and HoloLens, the system is able to offer a better operate experience by allowing the operator to teleoperate a robot within a mixed reality scene. Besides, we also design a simple writing task in this paper, which verifies the proposed system's validity.

关键词： Robot kinematics Virtual reality Manipulators Conferences Mechatronics Task analysis

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Position Tracking for Continuum Robots with Joint Limit Constraints

Position Tracking for Continuum Robots with Joint Limit Cons...

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International Conference on Unmanned systems and Artificial Intelligence

作者： Dengliang Lin Xin Dong Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Nottingham University Nottingham UK Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728158594

ISBN: (纸本)9781728158600

This paper presents a novel tip-following approach for real-time position tracking and avoiding obstacle of continuum robots with joint limit constraints. This type of hyper-redundant robot, which is more flexible and compliant to explore in complex and constrained environments, such as in pipeline or narrow entrance. However, tradictional method based on inverse kinematic model is difficult to control the end-effector of continuum robot to avoid abstcales in the constrained circumstance. Therefore a new tip-following method based on forward kinematic model is proposed to control the robot and make it inspect the environment. For the method, we use nonliner progamming approach to solve the optimization problem, which is used to find minimum of constrained nonlinear objective function to ensure that the end-effector of the robot follow the desired position with minimal error. In this paper, we employ a 24 DoF continuum robot with continuous backbone and compliant joint to the simulation, and it is testified that the proposed approch can ensure joint limit avoidance, track the end postion in real time and minimize the tracking errors.

关键词： hyper-redundant robots obstacle avoidance tip-following control kinematic model kinematics Robot Redundant robot Obstacle avoidance Continuum Location tracking Collision avoidance Joints end effectors

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Fuzzy rate analysis of operators and its applications in linear spaces

arXiv

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arXiv 2020年

作者： Zhang, Yijin Li, Honggang Jin, Maoming Lin, Zongbing Key Lab of Intelligent Analysis and Decision on Complex Systems Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Pass College of Chongqing Technology and Business University Chongqing401520 China Institute of Nonlinear Analysis Research Changjiang Normal University Chongqing400803 China School of Mathematics and Computer Science Panzhihua University Panzhihua617000 China

In this paper, a new concept, the fuzzy rate of an operator in linear spaces is proposed for the very first time. Some properties and basic principles of it are studied. Fuzzy rate of an operator B which is specific i... 详细信息

关键词： Membership functions

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