This paper considers the general filtering problem for a distinct class of two-dimensional (2-D) discrete linear systems, i.e. information propagation in two independent directions, known as discrete linear repetitive...
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This paper considers the general filtering problem for a distinct class of two-dimensional (2-D) discrete linear systems, i.e. information propagation in two independent directions, known as discrete linear repetitive processes which are of both system-theoretic and applications interest. In particular, new results on the design of filters with guaranteed levels of performance are developed. These take the form of algorithms for the design of an H infin and l 2 -l infin dynamic output feedback filter which guarantees that the resulting filtering error process is stable and has prescribed disturbance attenuation performance as measured by H infin and l 2 -l infin norms.
The unique characteristic of a repetitive process is a series of sweeps or passes through a set of dynamics defined over a finite duration known as the pass length. At the end of each pass, the process is reset and th...
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The unique characteristic of a repetitive process is a series of sweeps or passes through a set of dynamics defined over a finite duration known as the pass length. At the end of each pass, the process is reset and the next time through the output, or pass profile, produced on the previous pass acts as a forcing function on, an hence contributes to, the dynamics of the new pass profile. They are hence a class of systems with information propagation in two independent directions where here the dynamics over the finite pass length are described by a matrix linear differential equation and that from pass to pass has a discrete updating structure. This means that filtering/estimation theory/algorithms for, in particular, 2D discrete linear systems is not applicable. In this paper we solve a general filtering problem with a view toward use in the many applications where such action will be required.
The well-known conventional Kalman filter gives the optimal solution but requires an accurate system model and exact stochastic information. Thus, the Kalman filter with incomplete information may be degraded or even ...
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The well-known conventional Kalman filter gives the optimal solution but requires an accurate system model and exact stochastic information. Thus, the Kalman filter with incomplete information may be degraded or even diverged. In a number of practical situations, the system model and the stochastic information are incomplete. To solve this problem, a new adaptive fading Kalman filter (AFKF) using the forgetting factor has recently been proposed. This paper extends the AFKF to nonlinear system models to obtain an adaptive fading extended Kalman filter (AFEKF). The forgetting factor is generated from the ratio between the calculated innovation covariance and the estimated innovation covariance. Based on the analysis result of Reif for the EKF, the stability of the AFEKF is also analyzed.
作者：
Yi-Sheng HuangSheng-Luen ChungMu-Der JengDepartment of Aeronautical Engineering
Chung Cheng Institute of Technology National Defense University Tashi Taoyuan 335 Taiwan R.O.C. Department of Electrical Engineering
National Taiwan University of Science and Technology Taipei 106 Taiwan R.O.C. Department of Electrical Engineering
National Taiwan Ocean University Kellung 202 Taiwan R.O.C. MuDer Jeng received the Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute
Troy NY in 1992. Since August 1992 Dr. Jeng has been with National Taiwan Ocean University Keelung Taiwan where he is currently a full Professor at the Department of Electrical Engineering. His current research interests include Petri nets discrete event systems computer integrated manufacturing semiconductor factory automation embedded systems. Dr. Jeng is the author/co-author of over 120 book chapters journal papers and conference papers. Dr. Jeng received the Franklin V. Taylor Outstanding Paper Award from the IEEE Systems Man and Cybernetics Society in 1993. He was granted the Research Award by the National Science Council of Taiwan annually from 1994 to 2000. He is an Associate Editor for IEEE Transactions on Systems Man and Cybernetics-Part A IEEE Transactions on Robotics and Automation IEEE Transactions on Robotics and serves on the Editorial Board of International Journal of Computer Integrated Manufacturing. He has been a Guest Editor for eight leading journals. Dr. Jeng is the Chair of the Technical Committee on Discrete Event Systems of the IEEE SMC Society and the Founding Chair of the Technical Committee on Semiconductor Factory Automation of the IEEE Robotics and Automation Society. He served as the Exhibitions Chair of 2003 IEEE International Conference on Robotics and Automation and the Special Sessions Chair of 2004 IEEE International Conference on Networking Sensing and Control. He serves as a Program Co-Chair of 2005 IEEE International Conference on Networking Sensing and Control and the Organization Commit
Statechart has been utilized as a visual formalism for the modeling of complex and interactive systems for its illuminating features on describing properties of causality, concurrency, and synchronization. This paper ...
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Statechart has been utilized as a visual formalism for the modeling of complex and interactive systems for its illuminating features on describing properties of causality, concurrency, and synchronization. This paper presents the application of satechart to the modeling, design and implementation of an elevator system, whose system behavior involves aggregating complexity of state descriptions, and imposition of underlying control policy. Based on the operational flow of an elevator, we derive the associated statechart model by looking into the inherent hierarchical structure of the elevator. The advantage of the proposed approach is the clear presentation of system behavior in terms of conditions and events that cause the transitions in system dynamics. Implementation of the controlled elevator based on the modeled statechart is also presented.
We demonstrate electron transport in an enhancement mode in‐plane‐gate quantum dot transistor (IPGQDT). Deeply etched trenches allow large positive biases on the IPG with negligible leakage current Strong negative d...
We demonstrate electron transport in an enhancement mode in‐plane‐gate quantum dot transistor (IPGQDT). Deeply etched trenches allow large positive biases on the IPG with negligible leakage current Strong negative differential resistance (NDR) peaks and single electron tunneling are observed in a wide gate bias window. The position of the NDR peaks systematically moves with the change of the gate bias, suggesting that they originate from resonant tunneling through QD quantum states.
In this paper we consider an unstable biological process used for wastewater treatment. This anaerobic digestion ecosystem can have 2 locally stable steady states and one unstable steady state. We first study the mode...
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In this paper we consider an unstable biological process used for wastewater treatment. This anaerobic digestion ecosystem can have 2 locally stable steady states and one unstable steady state. We first study the model and characterise the attraction basin associated to the normal operating mode. In a second step we estimate the size of this attraction basin by using a simplified criterion that turns out to be a good approximation. Finally we apply the approach on a real anaerobic digestion plant, and we show that the proposed criterion allows to rapidly detect the conditions of a destabilisation.
In this work we present a comparative study, testing selected methods for clustering and classification of holter electrocardiogram (ECG). More specifically we focus on the task of discriminating between normal 'N...
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In this work we present a comparative study, testing selected methods for clustering and classification of holter electrocardiogram (ECG). More specifically we focus on the task of discriminating between normal 'N' beats and premature ventricular 'V' beats. Some of the tested methods represent the state of the art in pattern analysis, while others are novel algorithms developed by us. All the algorithms were tested on the same datasets, namely the MIT-BIH and the AHA databases. The results for all the employed methods are compared and evaluated using the measures of sensitivity and specificity.
In this paper we develop and apply a robust interval observer to estimate the unknown variables of uncertain chaotic systems. Considering that bounds of the uncertainties are known, we propose an observer that compute...
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ISBN:
(纸本)1424401704
In this paper we develop and apply a robust interval observer to estimate the unknown variables of uncertain chaotic systems. Considering that bounds of the uncertainties are known, we propose an observer that computes guaranteed upper and lower bounds for the unknown variables. We show that practical estimation (observer based synchronization) is asymptotically reached with bounded interval estimates. The method is applied to the synchronization of Chua's chaotic system
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