Interactive Digital Media Institute

Singapore, Singapore

Interactive Digital Media Institute

Singapore, Singapore
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Li Y.,National University of Singapore | Ge S.S.,Interactive Digital Media Institute | Ge S.S.,University of Electronic Science and Technology of China | Yang C.,University of Plymouth | And 2 more authors.
Proceedings - IEEE International Conference on Robotics and Automation | Year: 2011

In this paper, model-free impedance control is designed for the safe human-robot interaction. A passive impedance model is imposed on the robot and a control method is proposed to guarantee the robot dynamics governed by the target model. The proposed method does not require any model information except for upper bounds of system matrix. It is thus easy to apply to practical implementation. The rigorous analysis of the control performance and robustness is presented. The validity of the proposed method is verified on the six degrees-of-freedom (DOF) PUMA 560 robot arm through simulation. © 2011 IEEE.

Ge S.S.,University of Electronic Science and Technology of China | Ge S.S.,Interactive Digital Media Institute | Li Z.,South China University of Technology
IEEE Transactions on Automatic Control | Year: 2014

In this technical note, high dimensional integral Lyapunov functions are introduced for a class of MIMO nonlinear systems with unknown nonlinearities. First, adaptive state feedback control is presented based on the integral Lyapunov function. When only the output is measurable, by using a high-gain observer to estimate the derivative of the system output, adaptive output feedback control is also derived. The proposed control scheme provides a general approach to stabilize the MIMO plant without any restrictive assumptions. The control is continuous and ensures closed-loop stability and convergence of the tracking error to a small residual set. The size of the tracking error at steady state can be specified a priori and guaranteed by choosing the design parameters. © 1963-2012 IEEE.

Zhou J.,Yanshan University | Bao Z.,Interactive Digital Media Institute | Wang W.,University of New South Wales | Zhao J.,Yanshan University | Meng X.,Renmin University of China
VLDB Journal | Year: 2014

Keyword search over XML data has attracted a lot of research efforts in the last decade, where one of the fundamental research problems is how to efficiently answer a given keyword query w.r.t. a certain query semantics. We found that the key factor resulting in the inefficiency for existing methods is that they all heavily suffer from the common-ancestor-repetition problem. In this paper, we propose a novel form of inverted list, namely the IDList; the IDList for keyword k consists of ordered nodes that directly or indirectly contain k. We then show that finding keyword query results based on the smallest lowest common ancestor and exclusive lowest common ancestor semantics can be reduced to ordered set intersection problem, which has been heavily optimized due to its application in areas such as information retrieval and database systems. We propose several algorithms that exploit set intersection in different directions and with or without using additional indexes. We further propose several algorithms that are based on hash search to simplify the operation of finding common nodes from all involved IDLists. We have conducted an extensive set of experiments using many state-of-the-art algorithms and several large-scale datasets. The results demonstrate that our proposed methods outperform existing methods by up to two orders of magnitude in many cases. © 2013 Springer-Verlag Berlin Heidelberg.

Bidram A.,University of Texas at Arlington | Davoudi A.,University of Texas at Arlington | Lewis F.L.,University of Texas at Arlington | Ge S.S.,University of Electronic Science and Technology of China | Ge S.S.,Interactive Digital Media Institute
IEEE Transactions on Energy Conversion | Year: 2014

This paper proposes an adaptive and distributed secondary voltage control for microgrids with inverter-based distributed generators (DG). The proposed control is fully adaptive and does not require the information of DG parameters. Neural networks are used to compensate for the uncertainties caused by the unknown dynamics of DGs. The controller structure is fully distributed such that each DG only requires its own information and the information of its neighbors on the communication network. Therefore, this secondary control is associated with a sparse communication network. The effectiveness of the proposed methodology is verified for different loading, outage, and islanding scenarios, as well as variable communication structures in a microgrid setup. © 1986-2012 IEEE.

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