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检索条件"机构=Robotics and Control Laboratory Computer Engineering Division"

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Column Formation control of Multi-robot Systems with Input Constraints

Column Formation Control of Multi-robot Systems with Input C...

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IEEE Conference on Decision and control

作者： Xiaohan Chen Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781612848006

This paper is concerned with the column formation control of multi-robot systems that are subject to input constraints. A new leader-follower setup is proposed, under which the Lyapunov method can provide a simple controller in terms of two feedback parameters. It is shown that using an elliptic approximation to input constraints, the two feedback parameters can be obtained directly with a geometric analysis method. Moreover, a sufficient condition is presented for the leader robot to guarantee that the desired column formation can be achieved, with which a particular controller is designed by selecting two appropriate functions for the feedback parameters. Simulation results are included to verify the effectiveness of the proposed theoretical results.

关键词： Column formation control multi-robot systems leader-follower input constraints elliptic approximation

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Robust L_(2) - L_(infinity) Consensus control of the Second-order Multi-agent Systems with Time-delay

Robust L_(2) - L_(infinity) Consensus Control of the Second-...

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IEEE Conference on Decision and control

作者： Yan Cui Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781612848006

Robust L_(2) - L_(infinity) consensus control is studied for the second-order multi-agent systems with external disturbances and parameter uncertainties. By defining an appropriate controlled output, the consensus problem of the systems is transformed into a normal L_(2) - L_(infinity) control problem, and distributed state feedback protocols with time-delay are proposed. Sufficient conditions are established for the convergence to consensus of the network under fixed or switching topology. Numerical simulations are provided to demonstrate the effectiveness of our theoretical results.

关键词： Topology Europe

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Formation control of mobile robots with input constraints: An elliptic approximation approach

Formation control of mobile robots with input constraints: A...

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International Conference on control, Automation and Systems ( ICCAS)

作者： Xiaohan Chen Yingmin Jia Junping Du Fashan Yu The Seventh Research Division and Department of Systems and Control Beihang University BUAA Beijing China Beihang University Beijing CN Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper considers the problem of formation control for mobile robots which are subject to input constraints. The control strategy based on virtual robot tracking is proposed, which leads to a compact controller form in terms of two feedback parameters by Lyapunov method. The introduced elliptic approximation of input constraints brings much convenience to obtain suitable feedback parameters. It is show that the presented sufficient condition guarantees the existence of feasible feedback parameters. Moreover, guidelines for the selection of feedback parameters are provided with geometric analysis. Simulation results verify the effectiveness of the proposed control strategy.

关键词： Robot kinematics Lead Mobile robots Approximation methods Trajectory Educational institutions

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Adaptive Iterative Learning control for Uncertain Delay Systems Based on Model Matching Technique

Adaptive Iterative Learning Control for Uncertain Delay Syst...

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2011 American control Conference (ACC)

作者： Haixia Su Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

In this paper, an adaptive iterative learning control (ILC) scheme is proposed for trajectory tracking of uncertain delay systems based on model matching technique. The reference model is a delay system operating over in a finite time interval. An iterative model matching controller is designed and an iteration domain adaptive law is chosen to estimate the unknown parameters. It shows that the model matching technique can be applied in a straightforward method to ILC problem. A simulation example is included to illustrate the designed scheme.

关键词： Adaptation models Polynomials Adaptive systems Delay effects Delay systems

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Gaussian Mixture PHD Smoother for Jump Markov Models in Multiple Maneuvering Targets Tracking

Gaussian Mixture PHD Smoother for Jump Markov Models in Mult...

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2011 American control Conference (ACC)

作者： Wenling Li Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper presents a Gaussian mixture probability hypothesis density (GM-PHD) smoother for tracking multiple maneuvering targets that follow jump Markov models. Unlike the generalization of the multiple model GM-PHD filters, our aim is to approximate the dynamics of the linear Gaussian jump Markov system (LGJMS) by a best-fitting Gaussian (BFG) distribution so that the GM-PHD smoother can be carried out with respect to an approximated linear Gaussian system. Our approach is inspired by the recognition that the BFG approximation provides an accurate performance measure for the LGJMS. Furthermore, the multiple model estimation is avoided and less computational cost is required. The effectiveness of the proposed smoother is verified with a numerical simulation.

关键词： Target tracking Approximation methods Markov processes Covariance matrix Smoothing methods Radar tracking Computational efficiency

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Fuzzy rule based neuro-dynamic programming for mobile robot skill acquisition on the basis of a nested multi-agent architecture

Fuzzy rule based neuro-dynamic programming for mobile robot ...

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IEEE International Conference on robotics and Biomimetics

作者： Karigiannis, John N. Rekatsinas, Theodoros I. Tzafestas, Costas S. School of Electrical and Computer Engineering Division of Signals Control and Robotics National Technical University of Athens Zographou Athens Greece School of Computer Science University of Maryland College Park MD 20742 United States

ISBN: (纸本)9781424493173

Biologically inspired architectures that mimic the organizational structure of living organisms and in general frameworks that will improve the design of intelligent robots attract significant attention from the research community. Self-organization problems, intrinsic behaviors as well as effective learning and skill transfer processes in the context of robotic systems have been significantly investigated by researchers. Our work presents a new framework of developmental skill learning process by introducing a hierarchical nested multi-agent architecture. A neuro-dynamic learning mechanism employing function approximators in a fuzzified state-space is utilized, leading to a collaborative control scheme among the distributed agents engaged in a continuous space, which enables the multi-agent system to learn, over a period of time, how to perform sequences of continuous actions in a cooperative manner without any prior task model. The agents comprising the system manage to gain experience over the task that they collaboratively perform by continuously exploring and exploiting their state-to-action mapping space. For the specific problem setting, the proposed theoretical framework is employed in the case of two simulated e-Puck robots performing a collaborative box-pushing task. This task involves active cooperation between the robots in order to jointly push an object on a plane to a specified goal location. We should note that 1) there are no contact points specified for the two e-Pucks and 2) the shape of the object is indifferent. The actuated wheels of the mobile robots are considered as the independent agents that have to build up cooperative skills over time, in order for the robot to demonstrate intelligent behavior. Our goal in this experimental study is to evaluate both the proposed hierarchical multi-agent architecture, as well as the methodological control framework. Such a hierarchical multi-agent approach is envisioned to be highly scalable for the contr

关键词： Memory architecture

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Robust high-gain observer based output feedback control

Robust high-gain observer based output feedback control

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作者： Hyun, Chang-Ho Cho, Youngwan Park, Sungmoo Kim, Seungwoo Department of Computer Engineering Seokyeong University Korea Republic of Department of Electrical and Robotics Engineering Soonchunhyang University Korea Republic of Division of Electrical Electronic and Control Engineering Kongju National University Korea Republic of

ISBN: (纸本)9789604741755

This paper proposes a robust high-gain observer based output feedback controller for nonlinear systems. It is assumed that their states are unmeasurable. The proposed observer has the integrator of the estimation error in dynamics. It improves the performance of conventional high-gain observers and makes the proposed observer robust to noisy measurements, uncertainties and peaking phenomenon as well. Its convergence analysis is performed using Lyapunov theory and Lipschitz condition. In order to verify the effectiveness of the proposed scheme, it is applied to output feedback controllers and some comparative simulation result with the conventional observer based output feedback controllers and state feedback controllers is given.

关键词： State feedback

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Tracking control of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator

Tracking control of 3-wheels omni-directional mobile robot u...

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作者： Kim, Sangdae Hyun, Changho Cho, Youngwan Kim, Seungwoo Department of Electrical and Robotics Engineering Soonchunhyang University Korea Republic of Division of Electrical Electronic and Control Engineering Kongju National University Korea Republic of Department of Computer Engineering Seokyeong University Korea Republic of

ISBN: (纸本)9789604741755

Home service robot are not working in the fixed task such as industrial robot, because they are together with human in the same indoor space, but have to do in much more flexible and various environments. Most of them are developed on the base of the wheel-base mobile robot in the same method as a vehicle robot for factory automation. In these days, for holonomic system characteristics, omni-directional wheels are used in the mobile robot. A holonomic robot, using omni-directional wheels, is capable of driving in any direction. But trajectory control for omni-directional mobile robot is not easy. Especially, azimuth control which sensor uncertainty problem is included is much more difficult. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator. A trajectory controller for an omni-directional mobile robot, which each motor is controlled by an individual PID law to follow the speed command from inverse kinematics, needs a precise sensing data of its azimuth and exact estimation of reference azimuth value. It has imprecision and uncertainty inherent to perception sensors for azimuth. In this paper, they are solved by using fuzzy logic inference which can be used straightforward to perform the control of the mobile robot by means of the fuzzy behavior-based scheme already existent in literature. Finally, the good performance of the developed mobile robot is confirmed through live tests of path control task.

关键词： Mobile robots

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Modeling and analyzing nano-rod pushing with an AFM

Modeling and analyzing nano-rod pushing with an AFM

引用

2010 10th IEEE Conference on Nanotechnology, NANO 2010

作者： Hou, Jing Wu, Chengdong Liu, Lianqing Wang, Zhidong Dong, Zaili Dept. of Electrical and Computer Engineering Northeastern University Shenyang 110004 China State Key Laboratory of Robotics Shenyang Institute of Automation CAS Shenyang 110016 China Dept. of Advanced Robotics Chiba Institute of Technology Chiba Japan School of Information and Control Engineering Shenyang Jianzhu University Shenyang 110168 China

ISBN: (纸本)9781424470334

In developing nano-devices and nano-structures, traditional methodologies on MEMS meet the difficulty from the scale restriction. With the strategy of objects assembly, using AFM to handle nano-rods and other nano-objects is considered as an important and high potential technology in constructing nanostructures. However most of AFM only has one tip as the end effector and cannot control both translational and rotational motions during manipulation, this makes it be difficult to realize posture controllable manipulation especially in nano environment. In this paper, the behavior of nano-rod under pushing is theoretically analyzed and modeled. Viscous friction is incorporated in the model and the two situations that the pivot of the nanorod is either inside or outside the rod are addressed. By modeling, the pivot can be determined at each manipulation in real time, and the pushing points can be planned to realize posture controllable manipulation by using nano-hand strategy which is inspired by stable pushing theory of object manipulation in macro world, and to improve the reliability and the precision of manipulation. ©2010 IEEE.

关键词： Nanorods

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Fuzzy rule based neuro-dynamic programming for mobile robot skill acquisition on the basis of a nested multi-agent architecture

Fuzzy rule based neuro-dynamic programming for mobile robot ...

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IEEE International Conference on robotics and Biomimetics

作者： John N. Karigiannis Theodoros I. Rekatsinas Costas S. Tzafestas School of Electrical & Computer Engineering Division of Signals Control & Robotics National and Technical University of Athens Athens Greece School of Computer Science University of Maryland College Park MD USA

关键词： Mobile robots computer architecture Joints Robot kinematics Function approximation Collaboration

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