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IEEE International Conference on robotics and Biomimetics

作者： Pannatee Rakprayoon Peerayot Sanposh Nattapon Chayopitak Intelligent Mechatronics Automation Robotics and Control Laboratory Department of Electrical Engineering Kasetsart University Industrial Control and Automation Laboratory National Electronics and Computer Technology Center

ISBN: (纸本)9781457721366

This paper studies the real-time adaptive and repetitive control problem using the Desired Compensation Learning Law (DCLL) that has the advantage of robustness under the presence of unknown parameters with low memory requirement. The control structure of DCLL consists of a feedforward compensator that is designed by a linear combination of shape functions that is adaptable to parameter variations;hence the selection of appropriate shape functions plays an important role in the adaptive ability and accuracy of DCLL. In this study, the B-spline shape function is proposed to be used under the slowly updating scheme and the obtained results show that the robustness and accuracy of the tracking can be greatly improved even under payload variation and torque limits.

关键词： shape functions Repetitive controllers Self tuning splines (mathematics) Scheme Robot Manipulator adaptive capacity memory requirements Control Architecture Manipulators Unknown parameter Linear Combination

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Feature referenced tip localization enhanced by probability motion model for AFM based nanomanipulations

Feature referenced tip localization enhanced by probability ...

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IEEE International Conference on robotics and Biomimetics

作者： Shuai Yuan Lianqing Liu Zhidong Wang Ning Xi Yuechao Wang Zaili Dong Zhiyu Wang Zhibo Wang College of Information & Control Engineering of Shenyang Jianzhu University State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Department of Advanced Robotics Chiba Institute of Technology Department of Electrical and Computer Engineering Michigan State University

ISBN: (纸本)9781457721366

The spatial uncertainties of tip positioning due to the nonlinearity of the PZT scanner and thermal drift hinder the further application of the AFM based nanomanipulation. This paper brings forward feature referenced tip localization enhanced by probability motion model to reduce the spatial uncertainties. An improved motion model is probabilistically built by incorporating the PI model, the creep model and the thermal drift model. For calibrating the accurate model parameters, the statistical experiments are designed and performed. Then the tip position is optimally estimated by combining with a local scan based feature sensing method. The simulation and corresponding experiments are performed to illustrate the validity and feasibility of the calibrated parameters and the algorithm.

关键词： Atomic Force Microscopy terminal interface processor nonlinearity based model parameters Drift models

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Preface

Communications and Control Engineering

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Communications and Control engineering 2011年第9780857292551期 vii-xi页

作者： Sun, Zhendong Ge, Shuzhi Sam College Automation Science & Engineering Center for Control and Optimization South China University of Technology Guangzhou510640 China Robotics Institue and Institute of Intelligent Systems and Information Technology University of Electronic Science and Technology of China Chengdu China Department of Electrical and Computer Engineering The National University of Singapore Singapore Singapore

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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...

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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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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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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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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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Friction feedforward compensation and position feedforward in CNC machines

Friction feedforward compensation and position feedforward i...

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

作者： Wijin Suteeratanapirom Rapeepong Rattanawaorahirankul Chutima Laosapan Peerayot Sanposh Nattapon Chayopitak Kanokvate Tungpimolrut Hiroaki Kunieda TAIST Tokyo Technology China 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： Friction computer numerical control Metalworking machines Servomotors Three-term control Fasteners Rails Servomechanisms Torque control Error correction

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AFM tip on-line positioning by using the landmark in nano-manipulation

AFM tip on-line positioning by using the landmark in nano-ma...

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IEEE Nanotechnology Materials and Devices Conference (NMDC)

作者： Shuai Yuan Lianqing Liu Zhidong Wang Ning Xi Yuechao Wang Zaili Dong Zhiyu Wang Shenyang Jianzhu University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy and Sciences Shenyang China Chinese Academy of Sciences Beijing China Department of Advanced Robotics Chiba Institute of Technology Chiba Japan Department of Electrical and Computer Engineering Michigan State University USA

AFM has been proved to be a powerful nano-manipulation tool taking advantage of its ultra high resolution and precision. However the large spatial uncertainties associated with AFM tip positioning dual to the PZT nonlinearity and thermal drift are still challenging problems, which hinders its wide application especially in building complex structures In this paper, a probabilistic approach combined with the Kalman filter based localization algorithm is proposed to improve the accuracy of the tip positioning in the task space coordinate frame. A motion model based on the Prandtl-Ishlinskii (PI) model is established, the distribution of model error is statistically obtained through the experimental calibration process. In addition, to further reduce the tip position uncertainties, an environment measurement models is developed through sensing the landmark intermittently with local scanning method during manipulation. Both the simulations results and experimental results are presented to demonstrate the validity of the proposed method.

关键词： Kalman filters Position measurement Probabilistic logic Uncertainty Nanobioscience Accuracy Motion measurement

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Feature selection and classification of breast cancer on dynamic Magnetic Resonance Imaging by using artificial neural networks

Feature selection and classification of breast cancer on dyn...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Farzaneh Keivanfard Mohammad Teshnehlab Mahdi Aliyari Shoorehdeli Ke Nie Min-Ying Su Electrical and Computer Engineering Department Khaje Nasir Toosi University of Technology Tehran Iran Electrical and Computer Engineering Department Advanced Process Automation and Control (APAC) Khaje Nasir Toosi University of Technology Tehran Iran Center for Functional Onco-Imaging and Department of Radiological Sciences University of California Irvine CA USA

In this paper, a new feature selection and classification methods based on artificial neural network are applied to classify breast cancer on dynamic Magnetic Resonance Imaging (MRI). The database including benign and malignant lesions is specified to select the features and classify with proposed methods. It is collected from 2004 to 2006. A forward selection method is applied to find the best features for classification. Moreover, artificial neural networks such as Multilayer Preceptron (MLP) neural network, Probabilistic Neural Network (PNN) and Generalized Regression Neural Network (GRNN) are applied to classify breast cancer into two groups; benign and malignant lesions. Training and recalling neural networks are obtained with considering four-fold cross validation.

关键词： Fires Entropy Correlation Artificial neural networks Lesions Jacobian matrices Kinetic theory

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