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IEEE Conference on Decision and Control

作者： Chow Yin Lai Frank L. Lewis V. Venkataramanan Xuemei Ren Shuzhi Sam Ge Thomas Liew Centre for Life Sciences (CeLS) Graduate School for Integrative Sciences and Engineering (NGS) National University of Singapore Singapore Automation and Robotics Research Institute University of Texas Arlington Fort Worth TX USA Data Storage Institute Engineering Agency for Science Technology and Research Singapore Department of Automatic Control Beijing Institute of Technology Beijing China Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (纸本)9781424431236

In this paper, we show that the tracking performance of a hard disk drive actuator can be improved by using two adaptive neural networks, each of which is tailored for a specific task. The first neural network utilizes accelerometer signal to detect external vibrations, and compensates for its effect on hard disk drive position via feedforward action. In particular, no information on the plant, sensor and disturbance dynamics is needed in the design of this neural network disturbance compensator. The second neural network, designed to compensate for the pivot friction, uses a signum activation function to introduce nonlinearities inherent to pivot friction, thus reducing the neural network¿s burden of expectation. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Simulation results show that the tracking performance of the hard disk drives can be improved significantly with the use of both neural networks compared to the case without compensation, or when only one of the networks is activated.

关键词： Neural networks Friction Hard disks Actuators Adaptive systems Feedforward neural networks Accelerometers Signal detection Stability analysis Stability criteria

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Control of a biomimetic "soft-actuated" lower body 10dof exoskeleton

Control of a biomimetic "soft-actuated" lower body 10dof exo...

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作者： Costa, Nelson R.S. Caldwell, Darwin G. Centre for Robotics and Automation School of Computing Science and Engineering University of Salford M5 4WT United Kingdom

ISBN: (纸本)9783902661166

Currently many patients with brain/spinal cord/sport injuries or stroke, are confined to wheelchairs which results in many secondary conditions. Locomotor training attempts to encourage the patient to undertake walking exercises but the physical effort is such that there is poor compliance, as it requires a highly intensive and task-specific therapy approach. Powered Locomotor trainers aim to promote motor recovery, reducing this effort to a tolerable level encouraging higher levels of exercise, improved secondary health care and to obtain a better understanding of human motor walking gait. This paper will address the development and control of a lower limb exoskeleton for active assistive walking. Copyright © 2006 IFAC.

关键词： Muscle

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A target differentiation algorithm of multi-neural-network based on rough set for mobile robot

A target differentiation algorithm of multi-neural-network b...

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6th World Congress on Intelligent Control and automation, WCICA 2006

作者： Xin, Ma. Liu, Wei Li, Yibin Chen, Weidong Xi, Yugeng Centre for Robotics School of Control Science and Engineering Shandong University Jinan Shandong Province China Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)1424403324

Aiming at the uncertainty of sonar data in the problem of sonar-based target differentiation for mobile robot, the paper firstly presents a hierarchical reduction approach to reduce a sonar data set based on rough set theory. Then on the basis of the reduction, a multi-neural network based target differentiation algorithm is designed on the fact that the effective combination of multiple neural networks can increase the ability to pattern classification and generalization of the whole system. Parallel network architecture is adopted locally to increase the differentiation accuracy. And the average weighed strategy is applied to fuse the outputs of the parallel neural network classifiers to improve the robustness of the differentiation system to noise, physically plausible failure and missing sonar data situation. The simulation experiments prove that the new method combining with the traditional target differentiation algorithm can increase the accuracy of sonar-based target differentiation for mobile robot in indoor environments. © 2006 IEEE.

关键词： Mobile robots

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CONTROL OF A BIOMIMETIC “SOFT-ACTUATED” LOWER BODY 10DOF EXOSKELETON

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IFAC Proceedings Volumes 2006年第15期39卷 785-790页

作者： Nelson R.S. Costa Darwin G. Caldwell Centre for Robotics and Automation School of Computing Science and Engineering – University of Salford M5 4WT UK Phone: +*** – FAX +***

关键词： Exoskeleton walking control rehabilitation pneumatic muscle actuators muscle

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A Target Differentiation Algorithm of Multi-neural-network based on Rough Set for Mobile Robot

A Target Differentiation Algorithm of Multi-neural-network b...

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World Congress on Intelligent Control and automation (WCICA)

作者： Xin Ma Wei Liu Yibin Li Weidong Chen Yugeng Xi Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiaotong University Shanghai China Centre for Robotics School of Control Science and Engineering Shandong University Jinan Shandong China

关键词： Mobile robots Sonar Neural networks Uncertainty Set theory Algorithm design and analysis Pattern classification Fuses Noise robustness Working environment noise

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Multi-agent-based Auctions for Multi-robot Exploration

Multi-agent-based Auctions for Multi-robot Exploration

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World Congress on Intelligent Control and automation (WCICA)

作者： Xia Ma Fang Meng Yibin Li Weidong Chen Yugeng Xi Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiaotong University Shanghai China Centre for Robotics Department School of Control Science and Engineering Shandong University Jinan Shandong China

Aiming at improving the efficiency of the multi-robot exploration, this paper presents a novel auction algorithm based on the contact net protocol of the multi-agent theory. On the basis of the analysis of the limitations of the usual auction methods to the multi-robot exploration, the contract net protocol in the multi-agent theory is presented to design a completely distributive structure for the multi-robot exploration in order to increase the tolerance and reliability of the whole system. Then an improved multi-round single-item auction algorithm is presented to assign the frontiers to the multiple robots effectively. The theoretical analysis and the simulation experiments prove that the algorithm can lead to the effective coordination of multi-robot exploration with the decreasing computation compared to the combinatorial auctions

关键词： Robot kinematics Protocols Robustness robotics and automation Computational modeling Educational robots Automatic control Control engineering education Contracts Reliability theory

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Optimizing supervision and control for industrial furnaces: Predictive control based design 4

Optimizing supervision and control for industrial furnaces: ...

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4th IFAC Workshop Automatic Systems for Building the Infrastructure in Developing Countries, DECOM-TT 2004

作者： Dimirovski, Georgi M. Dinibütün, A. Talha Vukobratovic, Miomir K. Zhao, J. Faculty of Electrical Engineering MK-1000 Skopje SS Cyril and Methodius University Macedonia Computer Engineering Department Faculty of Engineering Acibadem Dogus University Zeamet Sk. 21 Kadikoy IstanbulTR-34722 Turkey Centre of Robotics and Flexible Automation Institute Mihailo Pupin Belgrade11000 Serbia School of Information Science and Engineering Institute of Control Theory Northeastern University Shenyang Liaoning110004 China

A systems re-engineering technique to integrated control and supervision for applications to industrial multi-zone furnaces has been elaborated by using known theories on generalized predictive control and nonlinear programming. This paper presents the derivation of optimizing equations and inequalities. The design is based on the use of general predictive control to provide optimized set-points under the presumption a well designed regulatory control was implemented at the executive level. Digital implementation of control functions are sought within standard computer process control platform for practical engineering and maintenance reasons. Copyright © 2004 IFAC.

关键词： Integrated control

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Optimizing Supervision and Control for Industrial Furnaces: Predictive Control Based Design

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IFAC Proceedings Volumes 2004年第19期37卷 17-28页

作者： Georgi M. Dimirovski A. Talha Dinibütün Miomir K. Vukobratovic J. Zhao SS Cyril and Methodius University Faculty of Electrical Engineering MK-1000 Skopje Republic of Macedonia Dogus University Computer Engineering Department Faculty of Engineering Acibadem Zeamet Sk. 21 Kadikoy TR-34722 Istanbul Turkey Institute “Mihailo Pupin” Centre of Robotics and Flexible Automation 11000 Belgrade Serbia and Montenegro Northeastern University School of Information Science and Engineering Institute of Control Theory Shenyang Liaoning 110004 P.R. of China

关键词： Complex time-delay processes generalized predictive control integrated control and supervision optimization set-point control

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A Lorentz-group based adaptive control for electro-mechanical systems

A Lorentz-group based adaptive control for electro-mechanica...

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Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of robotics in the the Next Millennium (Cat. No.01CH37180)

作者： J.K. Tar I.J. Rudas K. Jezernik J.F. Bito S.J. Torvinen Institute of Mathematical and Computational Sciences Budapest Polytechnic Budapest Hungary Centre of Robotics and Automation Budapest Polytechnic Hungary Faculty of Electrical Engineering and Computer Science Institute of Robotics University of Maribor Maribor Slovenia Dept. of Mechanical Eng. Institute of Production Engineering Tampere University of Technology Tampere Finland

An efficient approach for the adaptive control of approximately and partially known mechanical systems, like traditional soft computing, uses "uniform structures" for modeling, but these structures are obtained from certain Lie groups as the symplectic group or the generalized Lorentz group. This approach considerably reduces the number of free parameters in the model. Until now its efficiency was investigated for mechanical uncertainties and external dynamic interactions. In this paper the behavior of the electric drives are also included in the investigations. A 1-DOF mechanical system, a pendulum driven by a DC motor in a computed torque control, is investigated via simulation. The necessary torque is calculated from a formal primitive mechanical model and an adaptivity rule. For adaptivity real number scaling and the generalized Lorentz group elements are used. It is concluded that a single adaptive loop can compensate for the mechanical and the electrical uncertainties simultaneously.

关键词： Adaptive control Mechanical systems Uncertainty Convergence robotics and automation DC motors Robots Computer science Production engineering Neural networks

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