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Development of multi-fingered dexterous hand for grasping manipulation

Science China(Information Sciences) 2014年第12期57卷 76-85页

作者： LIN GuoDong LI ZhiJun LIU Lan SU Hang YE WenJun The Key Lab of Autonomous System and Network Control Ministry of EducationCollege of Automation Science and Engineering South China University of Technology School of Material Science and Engineering South China University of Technology Department of Mechanical and Industrial Engineering Concordia University

In this paper,a developed multi-fingered dexterous hand with flexible tactile skin is *** dexterous hand has 5-fingers with 6-DOFs and each finger is equipped with a small harmonic drive gear and a fine high-power mini *** achieve the goal of grasping with high accuracy,each fingertip is covered with the tactile array sensors for determination of the force between the finger and the grasped *** preliminary experiments are conducted to illustrate the performance of the grasping of the developed dexterous hand.

关键词： multi-fingered dexterous hand grasping tactile sensors

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Scheduling of Electric Vehicle Charging Request and Power Allocation at Charging Stations with Renewable Energy 33

Scheduling of Electric Vehicle Charging Request and Power Al...

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第三十三届中国控制会议

作者： LI Jingwei YANG Bo XU Yang CHEN Cailian GUAN Xinping ZHANG Weidong Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Electrical Engineering and Automation Shanghai Jiao Tong University

ISBN: (纸本)9781479947249

Smart grid, a concept proposed in 2003, is now attracting more and more attention because of its ability to integrate intensive information and renewable energy generating infrastructures. This paper focuses on scheduling charging process between multiple electric vehicles and charging stations in smart grid with renewable energy and storage devices. From the perspective of the whole system, the goal of minimizing the time average electricity cost with time-varying electricity price can be reached in this paper. With the participation of storage devices, charging-station-private renewable generation and electric vehicles power demands, we mathematically formulate a stochastic optimal problem and address it by employing Lyapunov optimization methods. Through mathematical derivation, stability of storage devices is achieved. Meanwhile, the upper bound for time average electricity cost can be calculated. The feature of our research is the independence on stochastic distribution of demand and renewable generation. Simulation results show the convergence of storage device state of charging（SOC） and illustrate the efficiency and performance of our algorithm.

关键词： Smart grid EV guidance renewable generation energy storage device Lyapunov optimization

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Cognitive Radio Enabled Reliable Transmission for Optimal Remote State Estimation in Multi-Sensor Industrial Cyber-Physical systems

Cognitive Radio Enabled Reliable Transmission for Optimal Re...

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IEEE/CIC International Conference on Communications in China

作者： Ling Lyu Cailian Chen Cunqing Hua Xinping Guan Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 P. R. China School of Information Security Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781509002443

This paper investigates the remote state estimation for the multi-sensor industrial cyber-physical systems (ICPSs) with the help of cognitive radio (CR) technology. The remote state estimator estimates the system states based on the measurements received from multi-sensor via the unreliable communication media, therefore, the performance of remote state estimation is up to the transmission reliability. In this paper, the redundant transmission is adopted to improve the reliability. Furthermore, the CR technology, which can intelligently discover the available spectrum opportunities in licensed bands, is exploited to alleviate the spectrum over-crowd problem aggravated by the redundancy design to improve the state estimation performance by. Specifically, we firstly formulate two CR enabled sequential optimization problems to improve the accuracy of state estimation and enhance the understanding of industrial plant. The primary one is to minimize the CR enabled estimation error subjected to the limited resource. The secondary one is to maximize the CR enabled best-effort data transmission volume subjected to the primary one's solutions. Secondly, a new sequence is constructed to approximate the limit-form objective function of the primary optimization problem. Finally, the two optimization problems are transformed into convex programming with the Lagrangian relaxation and Lagrangian dual decomposition techniques to reduce the computational complexity. Numerical results demonstrate that the CR technology reduces the mean square error of state estimation by about 40% and increases the volume of the best-effort data transmission by about 320%.

关键词： Industrial cyber-physical systems cognitive radio technology state estimation Kalman filter State estimation multi sensor Kalman filters Cognitive radio chromium power transmission reliability radio technology Mean square error Remote

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Experimental Verification of a Multi-robot Distributed control Algorithm with Containment and Group Dispersion Behaviors: the Case of Dynamic Leaders

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IEEE/CAA Journal of Automatica Sinica 2014年第1期1卷 54-60页

作者： Hejin Zhang Zhiyun Zhao Ziyang Meng Zongli Lin Department of Automation and Key Laboratory for System Control and Information Processing of Ministry of Education Shanghai Jiao Tong University the Access Linnaeus Centre School of Electrical Engineering Royal Institute of Technology Charles L. Brown Department of Electrical and Computer Engineering University of Virginia

This paper studies the containment and group dispersion control for a multi-robot system in the presence of dynamic leaders. Each robot is represented by a doubleintegrator dynamic model and a distributed control algorithm is developed to drive the multi-robot system to follow a group of dynamic leaders with containment and group dispersion behaviors. The effectiveness of the algorithm is then verified on a multi-robot control platform.

关键词： Heuristic algorithms Mobile robots Robot kinematics Trajectory Dispersion Decentralized control

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Consensus-Based Distributed Mean Square State Estimation

Consensus-Based Distributed Mean Square State Estimation

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American control Conference

作者： Carlos E. de Souza Michel Kinnaert Daniel Coutinho Department of Systems and Control Laboratorio Nacional de Computacao Cientifica - LNCC/MCTI Av. Getulio Vargas 333 Petropolis RJ 25651-075 Brazil Department of Control Engineering and System Analysis Universite Libre de Bruxelles (ULB) Brussels 1050 Belgium Department of Automation and Systems Universidade Federal de Santa Catarina PO Box 476 Florianopolis SC 88040-900 Brazil

ISBN: (纸本)9781479917730

This paper addresses the design of a distributed steady state filter for a sensor network. In the considered scenario, an estimate of the full system state is determined at each network node. The filter structure includes both measurement update terms from neighboring nodes, and a consensus term on the state estimates. The computation of the filter gains is recast as a convex optimization problem. Convergence of the estimation error variance is ensured at each network node and a guaranteed performance in the mean square sense is achieved. Extension of the method to linear parameter-varying systems yields a gain scheduled distributed filter.

关键词： network node mean square Filters linear parameter varying system Sensor networks Distribute State estimation Error measure measurement update

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Development and learning control of a human limb with a rehabilitation exoskeleton

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IEEE Transactions on Industrial Electronics 2014年第7期61卷 3776-3785页

作者： Lu, Renquan Li, Zhijun Su, Chun-Yi Xue, Anke Institute of Information and Control Hangzhou Dianzi University Hangzhou 310018 China Key Laboratory of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China Department of Mechanical and Industrial Engineering Concordia University Montreal QC H3G 1M8 Canada

This paper describes a novel development of a lower limber exoskeleton for physical assistance and rehabilitation. The developed exoskeleton is a motorized leg device having a total of 4 DOF with hip, knee, and ankle actuated in the sagittal plane. The exoskeleton applies forces and learns the impedance parameters of both robot and human. An adaptive control scheme by incorporating learning control approaches into the exoskeleton system is developed to help the leg movement on a desired periodic trajectory and handle periodic uncertainties with known periods. The proposed control approach does not require a muscle model and can be proven to yield asymptotic stability for a nonlinear muscle model and an exoskeleton model in the presence of bounded nonlinear disturbances (e.g., spasticity and fatigue). The performance of the controller is demonstrated through closed-loop experiments on human subjects. The experiments illustrate the ability of the exoskeleton to enable the leg shank to track single and multiple period trajectories with different periods and ranges of motion. © 2013 IEEE.

关键词： Muscle

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Implementation of Input Shaping control to Reduce Residual Vibration in Industrial Network Motion system

Implementation of Input Shaping Control to Reduce Residual V...

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International Conference on control, automation and systems

作者： Ha-Quang-Thinh Ngo Quoc-Chi Nguyen Won-Ho Kim Control and Automation Lab Department of Mechatronics Engineering Ho Chi Minh City University of Technology Department of Mechatronics Engineering Ho Chi Minh City University of Technology Department of Intelligent System Engineering Dong-Eui University

ISBN: (纸本)9781479999767

In this paper, a method to implement the input shaping control in Mechatrolink-III motion system is introduced. Firstly, the underdamped system is theoretically built by modeling. Then, the motion controller of Mechatrolink-III network is designed to apply the input shaper for reducing residual vibration in manufacturing machine. Later, the experimental beam is set-up to verify the effective performance of input shaping technique. The validity of the control strategy is practically performed by testing ZV, ZVD and ZVDD input shapers. Especially, the successful implementation provides an opportunity to apply the input shaper for multi-axes since Mechatrolink-III motion controller supports up to 32 axes.

关键词： Motion control Input shaping Mechatrolink-III Industrial network Residual vibration

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Vision-Based Kinematic Calibration of Spherical Robots

Vision-Based Kinematic Calibration of Spherical Robots

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RSI/ISM International Conference on Robotics and Mechatronics

作者： Pedram Agand Hamid D. Taghirad Amir Molaee Advanced Robotics and Automation System (ARAS) Industrial Control Center of Excellence (ICEE) Department of Systems and Control Faculty of Electrical Engineering K. N. Toosi University of Technology Iran

ISBN: (纸本)9781467372350

In this article, a method to obtain spatial coordinate of spherical robot's moving platform using a single camera is proposed, and experimentally verified. The proposed method is an accurate, flexible and low-cost tool for the kinematic calibration of spherical-workspace mechanisms to achieve the desired accuracy in position. The sensitivity and efficiency of the provided method is thus evaluated. Furthermore, optimization of camera location is outlined subject to the prescribed cost functions. Finally, experimental analysis of the proposed calibration method on ARAS Eye surgery Robot (DIAMOND) is presented;In which the accuracy is obtained from three to six times better than the previous calibration.

关键词： Kinematic Calibration Vision-Base Positioning Eye Surgery Robot Spherical Workspace

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Probabilistic constrained stochastic model predictive control for Markovian jump linear systems with additive disturbance 19

Probabilistic constrained stochastic model predictive contro...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Lu, Jianbo Xi, Yugeng Li, Dewein Cen, Lihui Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Department of Control Engineering Central South University Changsha Hunan Province410083 China

ISBN: (纸本)9783902823625

This paper is concerned with stochastic model predictive control for Markovian jump linear systems with additive disturbance, where the systems are subject to soft constraints on the system state and the disturbance sequence is finitely supported with joint cumulative distribution function given. By resorting to the maximal disturbance invariant set of the system, a model predictive control law is given based on a dynamic controller which is with guaranteed recursive feasibility and ensures the probabilistic constraints on the states. By optimizing the volume of the disturbance invariant set, the dynamic controller is given. The closed loop system under this control law is proven to be stable in the mean square sense. Finally, a numerical example is given to illustrate the developed results. © IFAC.

关键词： Stochastic models

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Formulation of MPC for multiplicative stochastic uncertainty by multi-step probabilistic sets 19

Formulation of MPC for multiplicative stochastic uncertainty...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Li, Jiwei Li, Dewei Xi, Yugeng Cen, Lihui Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Department of Control Engineering Central South University Changsha Hunan Province410083 China

ISBN: (纸本)9783902823625

This paper designs multi-step probabilistic sets for linear, discrete-time, stochastic systems with unbounded multiplicative noise and probabilistic constraints. Multi-step probabilistic sets strengthen IWPp by bringing more degrees of freedom to optimize the applicable region of finite-step probabilistic constraints, and extending the prediction horizon of IWPp to infinity for infinite-horizon probabilistic constraints. Conditions for multi-step probabilistic sets are then incorporated into a stochastic model predictive control algorithm to satisfy probabilistic constraints. Closed-loop mean-square stability is guaranteed by the algorithm. A numerical example shows the performance of the proposed algorithm. © IFAC.

关键词： Stochastic models

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