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检索条件"机构=Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering"

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Reducing stick-slip motion in one-dimensional nano manipulation by real-time feedback control

Reducing stick-slip motion in one-dimensional nano manipulat...

引用

2010 10th IEEE Conference on Nanotechnology, NANO 2010

作者： Zhang, Jing Miao, Lei Wu, Re-Bing Xi, Ning Li, Chun-Wen Wang, Yue-Chao Tarn, Tzyh-Jong Department of Automation Tsinghua University Beijing 100084 China Center for Quantum Information Science and Technology Tsinghua National Laboratory for Information Science and Technology Beijing 100084 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Beijing 110016 China Department of Electrical and Computer Engineering Michigan State University East Lansing MI 48824 United States Department of Electrical and Systems Engineering Washington University St. Louis MO 63130 United States

ISBN: (纸本)9781424470334

When a micro cantilever with a nanoscale tip is manipulated on a substrate with atomic roughness, e.g., pushing an atomic-scale sample or etching the surface of the substrate to draw desired patterns, the periodical lateral frictional forces with stochastic fluctuations will induce stick-slip motion of the cantilever tip, which may greatly influence the precision of the nano manipulation. To reduce such a stick-slip motion, we propose a feedback control strategy based on the position estimation of the cantilever tip to compensate the periodical frictional force. Numerical simulations show that the motion of the cantilever tip under feedback control can track the desired trajectory asymptotically. Our proposal can aL be extended to the case when the cantilever tip moves over a Gaussian-shape defection on the substrate and when the stochastic fluctuations in the lateral force are with non-zero correlation time. ©2010 IEEE.

关键词： Feedback control

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On asymptotic consensus value in directed random networks

On asymptotic consensus value in directed random networks

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IEEE Conference on Decision and Control

作者： Victor M. Preciado Alireza Tahbaz-Salehi Ali Jadbabaie Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA General Robotics Automation Sensing and Perception (GRASP) Laboratory Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA

ISBN: (纸本)9781424477456

We study the asymptotic properties of distributed consensus algorithms over switching directed random networks. More specifically, we focus on consensus algorithms over independent and identically distributed, directed random graphs, where each agent can communicate with any other agent with some exogenously specified probability. While different aspects of consensus algorithms over random switching networks have been widely studied, a complete characterization of the distribution of the asymptotic value for general asymmetric random consensus algorithms remains an open problem. In this paper, we derive closed-form expressions for the mean and an upper bound for the variance of the asymptotic consensus value, when the underlying network evolves according to an i.i.d. directed random graph process.

关键词： Eigenvalues and eigenfunctions Switches Markov processes Silicon Upper bound Closed-form solution Convergence

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Fuzzy-Bayesian network approach to genre-based recommender systems

Fuzzy-Bayesian network approach to genre-based recommender s...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Soheila Ashkezari-T Mohammad-R. Akbarzadeh-T Department of Computer Engineering Cognitive Computing Laboratory Center of Applied Research on Soft computing and Intelligent systems Ferdowsi University of Mashhad Mashhad Iran Departments of Electrical Engineering and Computer Engineering Cognitive Computing Laboratory Center of Applied Research on Soft computing and Intelligent systems Ferdowsi University of Mashhad Iran

The World Wide Web has created a new media for mass marketing that can also be highly customized to online customers' needs and expectations. Recommender systems (RS) play an important role in this area. Here, we aim to establish a genre-based collaborative RS to automatically suggest and rank a list of appropriate items (movies) to a user based on the user profile and the past voting patterns of other users with similar tastes. The contribution of this paper is using genre based information in a hybrid fuzzy-Bayesian network collaborative RS. The interest to the different genres is computed based on a hybrid user model. The similarity of like-minded users according to the fuzzy distance and also Pearson correlation coefficient is involved in a Bayesian network.

关键词： Motion pictures Mathematical model Collaboration Recommender systems Equations Computational modeling

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Adaptive predictive control of a class of discrete-time MIMO nonlinear systems with uncertain couplings

Adaptive predictive control of a class of discrete-time MIMO...

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作者： Yang, Chenguang Li, Yanan Ge, Shuzhi Sam Lee, Tong Heng Department of Bioengineering Imperial College London London SW7 2AZ United Kingdom Social Robotics Lab Interactive Digital Media Institute and Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore Institute of Intelligent Systems University of Electronic Science and Technology of China Chengdu 610054 China

ISBN: (纸本)9781424474264

In this paper, a novel adaptive predictive control is presented for a class of multi-input-multi-output (MIMO) nonlinear systems in block-triangular form with uncertain couplings of states/delayed states as well as inputs among subsystems. For each subsystem of the MIMO system, future states prediction is developed and using the predicted future states, adaptive predictive control is designed under certainty equivalence principal to compensate the parametric uncertainties in the couplings. To eliminate the functional uncertainties in the couplings, a novel compensation mechanism is developed for each subsystem. Under the proposed adaptive controls, all the signals in the closed-loop MIMO systems are guaranteed to be globally bounded. In addition, all the output tracking errors are guaranteed to converge to zeros. The effectiveness of the proposed control is demonstrated in the simulation. © 2010 AACC.

关键词： Couplings

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Fuzzy Nash equilibrium in fuzzy games using ranking fuzzy numbers

Fuzzy Nash equilibrium in fuzzy games using ranking fuzzy nu...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Alireza Chakeri Nasser Sadati Setareh Sharifian Department of Electrical Engineering Isfahan University of Technology Isfahan Iran Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada Intelligent Systems Laboratory Department of Electrical Engineering Sharif University of Technology Tehran Iran Electrical Engineering Department Isfahan University of Technology Isfahan Iran

In traditional game theory, the players play with policy of maximizing their payoffs. In real world, there are many situations where payoffs have uncertainty and are fuzzy in nature. In this paper, a new method for finding pure strategy Nash equilibriums, to realistically analyze the games with fuzzy payoffs is investigated. Using ranking fuzzy numbers, a fuzzy preference relation is constructed over payoffs. The priorities of payoffs are considered as the degree of being Nash equilibriums.

关键词： Games Nash equilibrium Fuzzy sets Pragmatics electrical engineering

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Parameter identification of a linear permanent magnet motor using particle swarm optimization

Parameter identification of a linear permanent magnet motor ...

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7th Annual International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2010

作者： Therdbankerd, Tithiwat Sanposh, Peerayot Chayopitak, Nattapon Fujita, Hideaki Department of Electrical Engineering Intelligent Mechatronics Automation Robotics and Control Laboratory Kasetsart University 50 Phahonyothin Rd. Ladyao Jatujak Bangkok 10903 Thailand Industrial Control and Automation Laboratory National Electronics and Computer Technology Center 112 Thailand Science Park Phahonyothin Rd. Klong 1 Klong Luang Pathumthani 12120 Thailand Department of Electrical and Electronic Engineering Tokyo Institute of Technology S3-18 2-12-1 Ookayama Meguro-ku Tokyo 152-8550 Japan

ISBN: (纸本)9789746724913

Accurate and effective parameter identification is an important engineering task in high performance control system design. One emerging approach to effectively identify such nonlinear or dynamic unknown parameters is to use Particle Swarm Optimization (PSO) algorithm. Linear Permanent Magnet (LPM) motor is a high performance actuator employed in many applications that require direct linear motion without mechanical transmission for high acceleration and accurate positioning. Therefore, accurate motor parameters are necessary to effectively control the LPM motors. This paper proposes a simple PSO based method with chirp inputs to identify the LPM motor's parameters. The simulations and experiments are conducted to verify the results and determine the effectiveness of the proposed method.

关键词： Parameter estimation

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Learning compliance control of robot manipulators in contact with the unknown environment

Learning compliance control of robot manipulators in contact...

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2010 IEEE International Conference on Automation Science and engineering, CASE 2010

作者： Li, Yanan Yang, Chenguang Ge, Shuzhi Sam Social Robotics Lab. NUS Graduate School for Integrative Sciences and Engineering National University of Singapore Singapore 119613 Singapore Department of Bioengineering Imperial College London London SW7 2AZ United Kingdom Department of Electrical and Computer Engineering Interactive Digital Media Institute National University of Singapore Singapore 117576 Singapore Institute of Intelligent Systems University of Electronic Science and Technology of China Chengdu 610054 China

ISBN: (纸本)9781424454471

In this paper, a control mechanism is presented to improve the compliance performance of the robot manipulator when it is in contact with the unknown environment. This mechanism guarantees that the dynamics of the whole system follows a target impedance model so that the desired compliance performance is obtained. In particular, under the assumption that the dynamics is periodic, a learning law is developed to estimate the unknown dynamics parameters. Besides, the proposed systematic learning control does not require the accurate force measurement. Its performance and robustness are discussed in details by the rigorous analysis. At last, the validity of the proposed method is verified by simulation. © 2010 IEEE.

关键词： Modular robots

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Friction feedforward compensation and position feedforward in CNC machines

Friction feedforward compensation and position feedforward i...

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7th Annual International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2010

作者： Suteeratanapirom, Wijin Rattanawaorahirankul, Rapeepong Laosapan, Chutima Sanposh, Peerayot Chayopitak, Nattapon Tungpimolrut, Kanokvate Kunieda, Hiroaki TAIST Tokyo Tech ICTES Program Department of Electrical Engineering Kasetsart University 50 Phahonyothin Rd. Ladyao Jatujak Bangkok 10903 Thailand Intelligent Mechatronics Automation Robotics and Control Laboratory Department of Electrical Engineering Kasetsart University 50 Phahonyothin Rd. Ladyao Jatujak Bangkok 10903 Thailand Industrial Control and Automation Laboratory National Electronics and Computer Technology Center 112 Thailand Science Park Phahonyothin Rd. Klong 1 Klong Luang Pathumthani 12120 Thailand Department of Electrical and Electronic Engineering Tokyo Institute of Technology S3-65 2-12-1 Ookayama Meguro-ku Tokyo 152-8550 Japan

ISBN: (纸本)9789746724913

This research proposes a method to eliminate friction effect and reduced tracking error on CNC milling machines. A CNC milling machine has many connected mechanical components which have friction effects such as ball screws and rails. To control servo motors which are used to drive X-Y table in CNC milling machine, the conventional PID controller is widely used. In this research, Panasonic motor driver is set to the torque control mode. To compensate the friction effects, the friction feedforward compensation method is proposed. Moreover, to reduce the position tracking error, position feedforward controller is used. The simulation and implementation of position control in one axis of PID with Friction Feedforward Compensation and Position Feedforward Controller (FFC-PFC) are presented.

关键词： Friction

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Nonlinear Model Predictive Control using sampling and goal-directed optimization

Nonlinear Model Predictive Control using sampling and goal-d...

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IEEE Conference on Control Technology and Applications (CCTA)

作者： Damion D. Dunlap Charmane V. Caldwell Emmanuel G. Collins Department of Mechanical Engineering and the Center for Intelligent Systems Control and Robotics (CISCOR) Florida Agricultural and Mechanical University Tallahassee FL USA Department of Electrical and Computer Engineering CISCOR of the FAMU-FSU COE USA Department of Mechanical Engineering CISCOR of the FAMU-FSU COE USA

In this paper a novel method called Sampling-Based Model Predictive Control (SBMPC) is proposed as an efficient MPC algorithm to generate control inputs and system trajectories. The algorithm combines the benefits of sampling-based motion planning with MPC while avoiding some of the major pitfalls facing both traditional sampling-based planning algorithms and traditional MPC. The method is based on sampling (i.e., discretizing) the input space at each sample period and implementing a goal-directed optimization method (e.g., A*) in place of standard numerical optimization. This formulation of MPC readily applies to systems with nonlinear dynamics and avoids the local minima which can limit the performance of MPC algorithms implemented using traditional, derivative-based, nonlinear programming. The SBMPC algorithm is compared with a more standard online MPC algorithm using cluttered environment navigation for an Ackerman steered vehicle and a set point problem for a nonlinear, continuous stirred-tank reactor (CSTR).

关键词： Optimization Planning Vehicles Prediction algorithms Trajectory Heuristic algorithms Predictive models

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Parameter identification of a Linear Permanent Magnet motor using Particle Swarm Optimization

Parameter identification of a Linear Permanent Magnet motor ...

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International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： Tithiwat Therdbankerd Peerayot Sanposh Nattapon Chayopitak Hideaki Fujita Intelligent Mechatronics Automation Robotics and Control Laboratory Department of Electrical Engineering Kasetsart University Bangkok Thailand Industrial Control and Automation Laboratory National Electronics and Computer Technology Center Klong Luang Pathum Thani Thailand Department of Electrical and Electronic Engineering Tokyo Institute of Technology Meguro Tokyo Japan

ISBN: (纸本)9781424456062;9789746724913

关键词： Parameter estimation Permanent magnet motors Particle swarm optimization Synchronous motors Signal processing robotics and automation Chirp intelligent robots Control systems Laboratories

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