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2010 49th IEEE Conference on Decision and control

作者： Lin Li 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)9781424477456

This paper is devoted to the problem of L_(2)-L_(infinity) control for a class of stochastic time-delay systems via observer-based feedback control. The considered observer contains no time-delay. The purpose is to design an observer-based feedback stabilizing controller such that the augmented closed-loop system is stochastically asymptotically stable with a prescribed L_(2)-L_(infinity) performance satisfied. Based on the stochastic stability theory, a delay-dependent sufficient condition is derived in terms of linear matrix inequalities (LMIs). The observer and controller design method is proposed, while the corresponding explicit expression for the observer and controller gain matrices is also given. Finally, numerical examples and simulation results are included to illustrate the effectiveness of the proposed results.

关键词： stochastic systems system clock time varying stability theory Stochastic delay systems controller gain Closed loop systems

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L_(2)-L_(infinity) Filter Design for Neutral Stochastic Time-Delay systems

L_(2)-L_(infinity) Filter Design for Neutral Stochastic Time...

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2010 49th IEEE Conference on Decision and control

ISBN: (纸本)9781424477456

This paper is concerned with the problem of L_(2)-L_(infinity) filtering for a class of neutral stochastic systems with both discrete and distributed time-varying delays. The purpose is focusd on the design of a full order filter such that the resulting filtering error system is stochastically asymptotically stable in the mean square with a prescribed L_(2)-L_(infinity) disturbance attenuation level satisfied. By employing Lyapunov functional and stochastic stability theory, a delay-dependent sufficient condition for the existence of such a filter is obtained in terms of linear matrix inequalities (LMIs). The desired filter can be obtained by solving two LMIs.

关键词： Stochastic delay systems Filters mean square filter design stochastic systems error system stability theory Delay systems Filtration

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A New Resampling Algorithm for Generic Particle Filters

A New Resampling Algorithm for Generic Particle Filters

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American control Conference

作者： X. Fu Y. Jia J. Du F. 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)9781424474264

This paper is devoted to the resampling problem of particle filters. We firstly demonstrate the performance of classical Resampling algorithm (also called as systematic resampling algorithm) using a novel metaphor, through which the existing defects of Resampling algorithm is vividly reflected simultaneously. In order to avoid these defects, the exquisite resampling (ER) algorithm is induced which involves some exquisite actions such as comparing the weights by stages and generating the new particles based on quasi-Monte Carlo method. Simulations indicate that the proposed ER algorithm can reduce the sample impoverishment effectively and improve the accuracy of estimation evidently, which confirm that ER algorithm is a competitive alternative to Resampling algorithm.

关键词： resampling algorithm Particle filters

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Kalman filtering with multiple nonlinear-linear mixing state constraints

Kalman filtering with multiple nonlinear-linear mixing state...

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IEEE Conference on Decision and control

作者： X. Fu Y. Jia J. Du F. Yu Seventh Research Division and the Department of Systems and Control Beihang University 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 is devoted to the problem of state estimation for a class of dynamic system with multiple nonlinear-linear (NL) mixing state constraints. A computational algorithm was developed by C. Yang and E. Blasch to incorporate a positive definite quadratic form equality constraint into the Kalman filtering for the ground vehicle tracking. However, when the target tracked in multidimensional space, a single positive definite quadratic form constraint is not enough due to the involvement of other surface such as hyperboloid, paraboloid, or even plane. A analytic method of incorporating multiple nonlinear-linear mixing state constraints into the Kalman filter is presented here, and a sufficient condition is obtained that guarantee the existence of solution. The constraints may be time varying. At each time step the unconstrained Kalman filter solution is projected onto the state constraints surface. This significantly improves the prediction accuracy of the filter. The use of this algorithm is demonstrated on a nonlinear-linear mixing spacecraft positioning problem.

关键词： Kalman filters Symmetric matrices State estimation Optimization Covariance matrix Noise

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Analysis of Two Robust Learning control Schemes in the Presence of Random Iteration-Varying Noise

Analysis of Two Robust Learning Control Schemes in the Prese...

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American control Conference

作者： Deyuan Meng 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)9781424474264

This paper deals with the design problem of robust iterative learning control (ILC), in the presence of noise that is varying randomly from iteration to iteration. Two ILC schemes are considered: one adopts the previous iteration tracking error (PITE) and the other adopts the current iteration tracking error (CITE), in the updating law. For both schemes, the convergence results are obtained by using a frequency-domain approach, and a comparison between them is presented from the viewpoints of the convergence condition, robustness against plant uncertainty, and delay compensation. It shows that sufficient conditions can be derived to bound the tracking error and make its expectation monotonically convergent in the sense of L_(2)-norm, which work effectively with robustness for all admissible plant uncertainties. Furthermore, the sufficient conditions for both schemes can also be formulated in terms of two complementary functions, which do not depend on the delay time as well as the plant uncertainty and, thus, make them convenient to be checked and solved using the frequency-domain tools. Numerical simulations are included to illustrate the effectiveness of the two proposed ILC schemes.

关键词： Iterative learning control monotonic convergence previous iteration tracking error current iteration tracking error random iteration-varying noise delay compensation delay compensation monotone convergence iterative methods Iterative learning control follow error Scheme design problems Delay time Sufficient conditions learning control

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A modified eigenvector method for blind deconvolution of MIMO systems using the matrix pseudo-inversion lemma

A modified eigenvector method for blind deconvolution of MIM...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Mitsuru Kawamoto Kiyotaka Kono Yujiro Inouye Koichi Kurumatani CREST Japan Science and Technology Agency Japan Information Technology Research Institute National Institute of Advanced Science and Technology (AIST) Koto-ku Tokyo Japan Kokuritsu Yonago Kogyo Koto Senmon Gakko Yonago Tottori JP Department of Electronic and Control Systems Engineering Shimane University Matsue Shimane Japan

Recently we have developed an eigenvector method (EVM) which can achieve the blind deconvolution (BD) for MIMO systems. The attractive features of the proposed algorithm are that the BD can be achieved by calculating the eigenvectors of a matrix and by using reference signals. However, the performance accuracy of the EVM depends highly on the computational result of the eigenvectors. In this paper, by modifying the EVM, we propose an algorithm which can achieve the BD without calculating the eigenvectors. Then the pseudo-inverse which is needed to carry out the BD is calculated by our proposed matrix pseudo-inversion lemma. Simulation results will be presented for showing the validity of the proposed method.

关键词： Deconvolution MIMO High performance computing control engineering Educational institutions control systems systems engineering and theory Computational modeling Proposals Blind equalizers

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Feature extraction for mental fatigue and relaxation states based on systematic evaluation considering individual difference

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2009年第2期129卷 302-307+16页

作者： Chen, Lanlan Sugi, Takenao Shirakawa, Shuichiro Zou, Junzhong Nakamura, Masatoshi Department of Automation East China University of Science and Technology Shanghai 200237 China Department of Advanced Systems Control Engineering Saga University Saga 840-8502 Japan National Center of Neurology and Psychiatry Tokyo Japan

Feature extraction for mental fatigue and relaxation states is helpful to understand the mechanisms of mental fatigue and search effective relaxation technique in sustained work environments. Experiment data of human states are often affected by external and internal factors, which increase the difficulties to extract common features. The aim of this study is to explore appropriate methods to eliminate individual difference and enhance common features. Mental fatigue and relaxation experiments are executed on 12 subjects. An integrated and evaluation system is proposed, which consists of subjective evaluation (visual analogue scale), calculation performance and neurophysiological signals especially EEG signals. With consideration of individual difference, the common features of multi-estimators testify the effectiveness of relaxation in sustained mental work. Relaxation technique can be practically applied to prevent accumulation of mental fatigue and keep mental health. The proposed feature extraction methods are widely applicable to obtain common features and release the restriction for subjection selection and experiment design. © 2009 The Institute of Electrical Engineers of Japan.

关键词： Feature extraction

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Dynamical modeling and identification of a GnRH neuron

Dynamical modeling and identification of a GnRH neuron

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作者： Csercsik, Dávid Szederkényi, Gábor Hangos, Katalin M. Farkas, Imre Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine HAS Budapest Hungary

ISBN: (纸本)9783902661494

GnRH neurons, as key elements of the reproductive neuroendocrine system, have important central regulating role in the dynamics of the hormonal cycle. A Hodgkin-Huxley type neural model is proposed in this paper, that takes into account up-to-date biological literature data related to ion channels. The proposed neuron model is highly nonlinear in parameters and the evaluation of the objective function is computationally flexpensive, therefore the asynchronous parallel pattern search (APPS) procedure has been used for identification. The model with high number of estimated parameters provides a qualitatively good fit of both voltage clamp and current clamp traces. © 2009 IFAC.

关键词： Neurons

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Model synthesis identification a Hodgkin-Huxley-type neuron model 10

Model synthesis identification a Hodgkin-Huxley-type neuron ...

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2009 10th European control Conference, ECC 2009

作者： Csercsik, David Szederkenyi, Gabor Hangos, Katalin M. Farkas, Imre Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine HAS Budapest Hungary

ISBN: (纸本)9783952417393

GnRH neurons are key elements of the reproductive neuroendocrine system and play important central regulating role in the dynamics of the hormonal cycle. A conductance-based Hodgkin-Huxley model structure is proposed in this paper in the form of nonlinear ordinary differential equations that is able to take into account up-to-date biological literature data related to ion channels. Measurement data were available for parameter estimation, which are originated from laboratory experiments done in the Institute of Experimental Medicine of the Hungarian Academy of Sciences in the form of whole cell patch-clamp recordings. The proposed neuron model is highly nonlinear in parameters and the evaluation of the objective function is computationally expensive, therefore the asynchronous parallel pattern search (APPS) procedure has been used for identification which is a gradient-free optimization method that can handle linear equality and inequality constraints and has advantageous convergence properties. The model with high number of estimated parameters provides a qualitatively good fit of both voltage clamp and current clamp traces. © 2009 EUCA.

关键词： Parameter estimation

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Reliable EOG signal based control approach with EEG signal judgement

Reliable EOG signal based control approach with EEG signal j...

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作者： Zhang, T. Chen, C. Nakamura, M. Department of Automation Tsinghua University Beijing 100086 China Department of Advanced Systems Control Engineering Saga University Saga 840-8502 Japan

ISBN: (纸本)9784990288037

This paper proposes a reliable EOG signal based control approach with EEG signal judgement. In this method, raw bio-neurological signals (including EOG and EEG) are first extracted and segmented in the preprocessing. The processed bio-neurological signals will be then evaluated by calculating feature parameters of these signals. Since in bio-neurological signals they may be contaminated by various kinds of artifacts, by means of feature parameters of bio-neurological signals, some artifacts of bio-neurological signals can be indicated. Thus, the bio-neurological signals contaminated with artifacts can not be adopted to generate control signals and judge the correctness of control signals. In the proposed method, in order to generate reliable control signal based on the EOG signal, EEG signal is adopted to assist to make judgement about the valid of EOG signal. With the proposed method, an EOG signal based control software platform has been implemented. By use of this platform, simulation work has been carried out to control the behavior of a robot. The simulation results verified the effectiveness of the proposed method. ©ISAROB 2009.

关键词： Neurology

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