This paper aims to present the design of a cloud computing-based equipment monitoring system (EMS), called CCEMS, for the CNC machine tool industry to illustrate the paradigm shift of EMSs from basing on the Internet ...
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It is difficult to build accurate mathematical models for nonlinear systems which suffer parametric uncertainty and heavy exogenous disturbance. Partial linearization was applied in this study to offset the effect of ...
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It is difficult to build accurate mathematical models for nonlinear systems which suffer parametric uncertainty and heavy exogenous disturbance. Partial linearization was applied in this study to offset the effect of losing nonlinear part of the system after complete linearization by introducing nonlinear functions into the linear model. On the condition that the nonlinear function satisfied constraints, Lyapunov function was employed to get the sufficient condition for the robust H ∞ optimal control law of the nonlinear system to exist. For the convenience of get the solution, the sufficient condition obtained was transformed into a problem of finding out feasible solution by linear matrix inequalities. Finally, a class of model simulation verifications was carried out, showing that proposed algorithm and designed control law were reasonable and effective.
Here we present an implementation of thermally-aware DVFS governor in a form of Linux 3.2 module. Our thermal governor operates by reading digital thermal sensors placed in CPU cores and pro-actively adjusting operati...
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Here we present an implementation of thermally-aware DVFS governor in a form of Linux 3.2 module. Our thermal governor operates by reading digital thermal sensors placed in CPU cores and pro-actively adjusting operating frequency of individual cores to maintain temperatures below given threshold. We evaluate our method using state-of-the-art parallel benchmarks from PARSEC suite. Apart from evaluation of our thermally-aware DVFS governor, we present insights into operation of a modern high-performance CPU with 6 cores and 2 hardware threads per core.
We consider a controllable linear time invariant model in state space of dimension n which might be the Jacobian linearization of a nonlinear model. Alternatively it may arise from a preceding input-output or input-st...
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We consider a controllable linear time invariant model in state space of dimension n which might be the Jacobian linearization of a nonlinear model. Alternatively it may arise from a preceding input-output or input-state linearization. The usual objective for such systems is to stabilize an equilibrium. However, it might as well be interesting to have a stable limit cycle around the equilibrium. So far, limit cycles are often studied in the context of nonsmooth dynamics. In contrast, our approach results in a smooth and simple feedback. The first step is to impose a pair of purely imaginary eigenvalues to the system while the second one is to construct a bilinear form with which the resulting oscillations can be stabilized at a given amplitude.
Temperature is among the most important factors limiting CPU performance. To ensure stable and reliable operation temperature has to be limited. In this paper we present a method for predicting temperature of a multi-...
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Temperature is among the most important factors limiting CPU performance. To ensure stable and reliable operation temperature has to be limited. In this paper we present a method for predicting temperature of a multi-core microprocessor based on it's high-level thermal model. Temperature prediction is then utilised in a Dynamic Thermal Management algorithm that can exploit performance optimisation opportunities while ensuring operation below temperature limit. The DTM algorithm uses frequency and voltage scaling of the CPU cores and task migration and was evaluated on a physical computer with a quad-core CPU.
In this paper, a hierarchical neural network with cascading architecture is proposed and its application to classification is analyzed. This cascading architecture consists of multiple levels of neural network structu...
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In the paper two approaches of parallelization for solving optimal control problems of ODE and index-1 DAE systems were presented and discussed. DAE Optimization Problem can be treated by Direct Nonlinear Programming ...
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In the paper two approaches of parallelization for solving optimal control problems of ODE and index-1 DAE systems were presented and discussed. DAE Optimization Problem can be treated by Direct Nonlinear Programming Approach in two manners, known as Sequential Approach and Simultaneous Approach. Simultaneous Approach seems to be more reliable, because provides initial states in periods and discretized control variables. Therefore there is a possibility of efficient use of Optimization with multiple shooting, which was developed to handle unstable DAE systems. In the article some parallelization methods of the Sequential Quadratic Programming were discussed and compared both in the Jacobian calculation and the numerical integration of DAE models. Augmented objective function, based on Mathematical Programming with Complementarity Constraints, was proposed. The illustrative simulations of Catalyst Mixing Problem were performed in MATLAB, which is a commonly known programming environment.
This paper overviews recent advances in the field of switched fuzzy systems, switched systems whose subsystems are fuzzy systems, followed by the comparative study for this kind of systems. Starting with the basic ide...
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Wireless sensor networks (WSNs) are autonomous ad hoc networks designed and developed for potential applications in monitoring, surveillance, security, etc. The sensor devices that are battery powered should have life...
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Wireless sensor networks (WSNs) are autonomous ad hoc networks designed and developed for potential applications in monitoring, surveillance, security, etc. The sensor devices that are battery powered should have lifetime of months or years. Therefore, energy efficiency is a crucial design challenge in WSN. In this paper the energy efficient communication techniques, i.e., activity control and power control protocols are presented and discussed. We focus on the implementation of energy aware algorithm for WSN - Geographical Adaptive Fidelity (GAF) - in our testbed network formed by the Maxfor devices. The results of experiments confirm significant energy savings that lead to network lifetime increase.
An object tracking algorithm based on SURF is presented in this paper. Interest points are detected by SURF detector in reference region which is located in the first frame manually. In the following sequences, the SU...
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An object tracking algorithm based on SURF is presented in this paper. Interest points are detected by SURF detector in reference region which is located in the first frame manually. In the following sequences, the SURF feature points are extracted in a larger window which is selected as test region. In the matching stage, we calculate the Euclidean distance between the descriptor vectors of interest points in the test image and ones in the reference image. The proposed algorithm is implemented on an embedded platform with TI's DM6446 high performance processor. The experimental results show that our system implements a real-time tracking with robustness against appearance variations, scale change, and cluttered scenes.
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