UTMAC is an object-oriented C++ class library, developed for design, implementation and simulation of multi-agent controllers. Using UTMAC, the control problem under analysis should be decomposed into several partial ...
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UTMAC is an object-oriented C++ class library, developed for design, implementation and simulation of multi-agent controllers. Using UTMAC, the control problem under analysis should be decomposed into several partial sub-problems to be solved by controller-agents, which can be implemented as reusable entities. UTMAC uses a non-centralized simulation scheme in which cash agent simulates itself. In this paper the structure of UTMAC is explored and design of a simple reusable multi-agent controller is provided to illustrate the work and show the convenience of design and implementation.
The paper is devoted to the problem of modeling demand for inventory management of slow-moving items in the case of reporting errors. It is proposed a generalization of the beta-binomial demand model that takes into a...
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The paper is devoted to the problem of modeling demand for inventory management of slow-moving items in the case of reporting errors. It is proposed a generalization of the beta-binomial demand model that takes into account possible reporting errors in the learning sample. For the new model, there are developed identification and forecasting algorithms that provide consistent estimators of the model parameters and mean square optimal forecasts. The efficiency of the proposed approach is illustrated by an application example for slow-moving car parts.
This paper focuses on the nano-scale analysis of the mechanical properties of polymer and carbon nanotubes (CNT) embedded MEMS devices using the probe tip of the atomic force microscope (AFM).The mechanical properties...
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This paper focuses on the nano-scale analysis of the mechanical properties of polymer and carbon nanotubes (CNT) embedded MEMS devices using the probe tip of the atomic force microscope (AFM).The mechanical properties of the surfaces of layered materials were investigated by using nanoindentation produced with the tips of an AFM. Experiment results indicated the bending characteristics of the device and also the Young's modulus of the CNT embedded micro structure. Our objective was to determine the nano-scale mechanical properties and piezoresistivity of bulk carbon nanotubes using the local probe manipulation.
Our research group, interested in outdoor scenes, has developed a methodology to register a CAD model of a city, with images taken with video cameras installed in a car, while driving city streets. So, we can merge vi...
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The magnetic fields of a linear induction motor (LIM) with cage-type secondary are analyzed using finite element method (FEM) according to the variation of the moving secondary position. Thus thrust and attraction for...
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This paper describes an implementation of the 9th-order Bessel filter using a new linear operational transconductance amplifier (OTA). To improve the linearity of the OTA, we employ a mobility compensation circuit. Th...
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This paper addresses the problem of robust filtering for uncertain linear signal models affected by time delays in the state. Uncertainty is structured and the model is assumed to lie in a given bounded polyhedral set...
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ISBN:
(纸本)0780379241
This paper addresses the problem of robust filtering for uncertain linear signal models affected by time delays in the state. Uncertainty is structured and the model is assumed to lie in a given bounded polyhedral set. The main innovation is the use of a nonrational filter, that is, a filter that also contains delays in the filter state. Robust filtering performance is evaluated using the H2 or the H∞ norm. The performance conditions are delay independent, and provide convex filtering design problems which are convex optimization problems with linear matrix inequalities constraints.
In this paper is proposed a robust higher-order iterative learning control (ILC) algorithm for discrete-time systems. In contrast to conventional discrete-time learning methods, the proposed learning algorithm is cons...
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In this paper is proposed a robust higher-order iterative learning control (ILC) algorithm for discrete-time systems. In contrast to conventional discrete-time learning methods, the proposed learning algorithm is constructed based on both time-domain performance and iteration-domain performance. Also, the proposed learning algorithm use more than one past error in the iteration-domain. It is proved that the proposed method has robustness in the presence of external disturbances and, in absence of all disturbances, the convergence of the proposed learning algorithm is guaranteed. A numerical example is given to show the robustness in the presence of state disturbance and convergence property according to parameters change.
The paper presents results achieved during realization of the international project DAMADICS (Development and Application of Methods for Actuator Diagnosis in Industrial control Systems). The proposed fault detection ...
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In this paper, first we survey Fault Detection and Isolation (FDI) for nonlinear systems. A necessary condition for the problem to be solvable is derived in terms of an unobservability distribution, which is computabl...
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