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New features of Easy Java Simulations for 3D Modeling

IFAC Proceedings Volumes 2010年第24期42卷 250-255页

作者： Carlos A. Jara Francisco Esquembre Francisco A. Candelas Fernando Torres Sebastián Dormido Department of Physics System Engineering and Signal Theory University of Alicante Alicante Spain (e-mail:{carlos.jara francisco.candelas fernando.torres}@ua.es) Department of Mathematics University of Murcia Murcia Spain (e-mail: fem@um.es) Department of Computer Science and Automatic Control UNED University Madrid Spain (e-mail: sdormido@dia.uned.es)

This paper presents a new interface framework which has been added to Easy Java Simualtions' environment in order to improve its graphical features for 3D modeling. These new 3D capabilities provide users a set of new view elements which can be used to develop models with a high degree of reality. In this way, Easy Java Simulations becomes a powerful tool to easily and quickly create 3D realistic simulations.

关键词： computer simulation modeling programming environment software tool virtual reality

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Multiple-atlas-based automatic sementation of hippocampus for lateralization in temporal lobe epilepsy

Multiple-atlas-based automatic sementation of hippocampus fo...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi-Asl Kourosh Jafari-Khouzani Hamid Soltanian-Zadeh Image Analysis Laboratory Department of Diagnostic Radiology Henry Ford Health System Detroit MI USA School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424441259

We introduce a 3D segmentation framework which uses principal shapes. The probabilistic energy function of the method is defined based on intensity, tissue type, and location information of the structures using a multiple atlas method. For intensity information, nonparametric probability density function is used which considers intensity relation of different structures. To find a local minimum of the energy function, a two-step optimization strategy is used. In the first step, shape parameters are optimized based on the analytic derivatives of the energy function. In the second step, shapes of the structures are fine-tuned using a level set method. The proposed method is shown to be superior to some popular methods in the literature using a dataset of 64 patients with mesial temporal lobe epilepsy. In addition, the method can be used for lateralization with accuracy close to that of manual segmentation.

关键词： Hippocampus Temporal lobe Epilepsy Image segmentation Principal component analysis Shape control Probability density function Level set Skull Algorithm design and analysis

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Fuzzy dynamic characteristic modeling and intelligent adaptive control for complex spacecraft

Fuzzy dynamic characteristic modeling and intelligent adapti...

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World Congress on Intelligent control and Automation (WCICA)

作者： Xiong Luo Song Hu Zengqi Sun Xintao Qiu School of Information Engineering Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing China State Key Laboratory of Intelligent Technology and System Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China

Because of strong coupling, nonlinear, and time-varying characteristics, it is difficult to control complex spacecraft. By means of combining with controlled object dynamics and performance requirements, characteristic modeling and control approach is an effective way to solve this problem. Aimed at the flexible satellites described by using characteristic modeling approach, with the help of fuzzy rules, fuzzy dynamic characteristic modeling method and intelligent adaptive controller are designed to control this complex spacecraft. Meanwhile, based on the satellite system simulation platform, we validate the correctness and efficiency of the proposed modeling and control method by comparing with the simulation results of the other similar methods.

关键词： Adaptation model Laboratories Satellites Space vehicles Intelligent control Artificial intelligence Information science

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Dynamic modeling and tracking control of fuel filled space robotic system with flexible manipulators

Dynamic modeling and tracking control of fuel filled space r...

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International Symposium on systems and control in Aerospace and Astronautics (ISSCAA)

作者： Xinxin Yang Xiong Luo Fuchun Sun Fengge Wu Huaping Liu School of Information Engineering Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing China State Key Laboratory of Intelligent Technology and System Department of Computer Science and TechnologyTsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China

In recent years, dynamics model and control of space robot system are the hot topics in the research field. In this paper, a new dynamics model and control strategy of space robotic system with a flexible manipulator and a liquid fuel tank are investigated. Based on Lagrange equation method, the dynamics model of the space robotic system coupling with liquid sloshing, flexibility vibration and base movement is derived. The elastic deflection of the flexible manipulator is described by the assumed mode method and equivalent mechanical model is adopted instead of liquid sloshing under the environment of low-gravity. The inverse dynamics control algorithm combined with PD control method is performed to solve the trajectory tracking problem. Some simulation results are given to verify the effectiveness of the proposed method.

关键词： Mathematical model Aerospace electronics Manipulator dynamics Equations Space vehicles

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A boundary method for outlier detection based on support vector domain description

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Pattern Recognition 2009年第1期42卷 77-83页

作者： Guo, S.M. Chen, L.C. Tsai, J.S.H. Department of Computer Science and Information Engineering National Cheng-Kung University Tainan 701 Taiwan Control System Laboratory Department of Electrical Engineering National Cheng-Kung University Tainan 701 Taiwan

The support vector domain description (SVDD) is a popular kernel method for outlier detection, which tries to fit a class of data with a sphere and uses a few target objects to support its decision boundary. The problem is that even with a flexible Gaussian kernel function, the SVDD could sometimes generate such a loose decision boundary that the discrimination ability becomes poor. Therefore, a computationally intensive procedure called kernel whitening is often required to improve the performance. In this paper, we propose a simple post-processing method which tries to modify the SVDD boundary in order to achieve a tight data description with no need of kernel whitening. With the derivation of the distance between an object and its nearest boundary point in input space, the proposed method can efficiently construct a new decision boundary based on the SVDD boundary. The improvement from the proposed method is demonstrated with synthetic and real-world datasets. The results show that the proposed decision boundary can fit the shape of synthetic data distribution closely and achieves better or comparable classification performance on real-world datasets. © 2008 Elsevier Ltd. All rights reserved.

关键词： Data description

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Optimal control for deterministic hybrid systems using dynamic programming

Optimal control for deterministic hybrid systems using dynam...

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作者： Rungger, Matthias Stursberg, Olaf Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Germany

ISBN: (纸本)9783902661593

Dynamic programming provides a method to solve hybrid optimal control problems. This contribution extends existing numerical methods originally developed for purely continuous systems, to a class of hybrid systems with autonomous as well as controlled switching behavior. The hybrid dynamics is approximated by a locally consistent discrete Markov decision process. The original optimal control problem is then reformulated for the Markov decision process and solved by standard dynamic programming methods. The convergence of the discrete approximation to the original problem is ensured. The viability of the numerical scheme is illustrated by a two gear transmission system used previously in literature.

关键词： Markov processes

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A communication-based distributed model predictive control scheme with time-varying consistency constraints 10

A communication-based distributed model predictive control s...

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2009 10th European control Conference, ECC 2009

作者： Dold, Johannes Stursberg, Olaf Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Germany

ISBN: (纸本)9783952417393

A communication-based distributed model predictive control scheme for a set of dynamically decoupled autonomous systems (agents) is proposed. The individual dynamics are described by discrete-time linear systems. Locally, each agent obeys a model predictive controller which minimizes a given local cost-function. Coupling between the agents occurs only through state-constraints. It is assumed that an initial feasible solution for the centralized optimization problem can only be found in a suboptimal manner due to computational limits. Then, the agents can decrease their local costs by replanning in each time step. This has to be done in a consistent way which is obtained by communicating local predicted trajectories under consideration of communication delays. © 2009 EUCA.

关键词： Cost functions

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Hierarchical hybrid modeling and control of flexible manufacturing systems 10

Hierarchical hybrid modeling and control of flexible manufac...

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2009 10th European control Conference, ECC 2009

作者： Paschedag, Tina Rungger, Matthias Ding, Hao Stursberg, Olaf Institute of Control and System Theory Department of Electrical Engineering and Computer Science University of Kassel Germany

ISBN: (纸本)9783952417393

In current manufacturing systems, short times for product development and ramp-up as well as high production rates and customized products are of increasing importance. To push the efficiency (and thus the economic gain) of production further, recent investigations combine aspects of flexible manufacturing systems with modeling and optimization techniques from the hybrid systems domain. Within this context, the contribution of this paper is two-fold: (1) a hierarchical modeling scheme is presented which suitably represents the plant dynamics on two distinct levels of detail comprising timed and hybrid automata, (2) an approach to adapt production online to changes in product specifications or production constraints by combining high-level generation of optimal production schedules with low-level learning- and model-based control. © 2009 EUCA.

关键词： Flexible manufacturing systems

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Extended Kalman filtering of point process observation

Extended Kalman filtering of point process observation

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Yousef Salimpour Hamid Soltanian-Zadeh Mohammad D. Abolhassani Neuroscience and Neuroengineering in School of Cognitive Sciences Institute of Studies in Fundamental Sciences IPM and Research Group for Brain and Cognitive Sciences School of Medicine Shahid Beheshti University Tehran Iran Department of Radiology Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence CIPCE Department of Electrical and Computer Engineering University of Tehran Tehran Iran Tehran University of Medical Sciences Tehran Tehran IR

A temporal point process is a stochastic time series of binary events that occurs in continuous time. In computational neuroscience, the point process is used to model neuronal spiking activity; however, estimating the model parameters from spike train is a challenging problem. The state space point process filtering theory is a new technique for the estimation of the states and parameters. In order to use the stochastic filtering theory for the states of neuronal system with the Gaussian assumption, we apply the extended Kalman filter. In this regard, the extended Kalman filtering equations are derived for the point process observation. We illustrate the new filtering algorithm by estimating the effect of visual stimulus on the spiking activity of object selective neurons from the inferior temporal cortex of macaque monkey. Based on the goodness-offit assessment, the extended Kalman filter provides more accurate state estimate than the conventional methods.

关键词： Mathematical model Equations Kalman filters Neurons Computational modeling Estimation

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Nonlinear system control using adaptive neural fuzzy networks based on a modified differential evolution

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IEEE Transactions on systems, Man and Cybernetics Part C: Applications and Reviews 2009年第4期39卷 459-473页

作者： Chen, Cheng-Hung Lin, Cheng-Lin Lin, Chin-Teng Department of Electrical and Control Engineering National Chiao-Tung University Hsinchu 300 Taiwan Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taiping City 411 Taiwan Department of Computer Science Department of Electrical and Control Engineering National Chiao-Tung University Hsinchu 300 Taiwan Brain Research Center University System of Taiwan Hsinchu 300 Taiwan

This study presents an adaptive neural fuzzy network (ANFN) controller based on a modified differential evolution (MODE) for solving control problems. The proposed ANFN controller adopts a functional link neural network as the consequent part of the fuzzy rules. Thus, the consequent part of the ANFN controller is a nonlinear combination of input variables. The proposed MODE learning algorithm adopts an evolutionary learning method to optimize the controller parameters. For design optimization, a new criterion is introduced. A hardware-in-the loop control technique is developed and applied to the designed ANFN controller using the MODE learning algorithm. The proposed ANFN controller with the MODE learning algorithm (ANFN-MODE) is used in two practical applications-the planetary-train-type inverted pendulum system and the magnetic levitation system. The experiment is developed in a real-time visual simulation environment. Experimental results of this study have demonstrated the robustness and effectiveness of the proposed ANFN-MODE controller. © 2009 IEEE.

关键词： controllers

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