• The Journal of Natural Sciences
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• v.7
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• pp.115-120
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• 1995

Imprecise computation has been suggested as a promising model of real-time computing in order to deal with timing constraints imposed by the environment. However, the theoretical foundation of the technique has not been fully explored. To address this, a decision-theoretic foundation of imprecise computation is proposed. The main benefit of such a treatment is that it enables the qualitative assumptions underlying imprecise computation techniques to be explicitly stated in a formal way. The theoretical foundation laid out in this paper, hence, will not only enable the justification of using imprecise computation techniques for a real-time application, but will also facilitate the development of extended techniques for more complexs real-time systems.

• Journal of Power Electronics
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• v.10 no.6
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• pp.739-748
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• 2010

The increased integration of fuel cells with power electronics, critical loads, and control systems has prompted recent interest in accurate electrical terminal models of the polymer electrolyte membrane (PEM) fuel cell. Advancement in computing technologies, particularly parallel computation techniques and various real-time simulation tools have allowed the prototyping of novel apparatus to be investigated in a virtual system under a wide range of realistic conditions repeatedly, safely, and economically. This paper builds upon both advancements and provides a means of optimized model construction boosting computation speeds for a fuel cell model on a real-time simulator which can be used in a power hardware-in-the-loop (PHIL) application. Significant improvement in computation time has been achieved. The effectiveness of the proposed model developed on Opal RT's RT-Lab Matlab/Simulink based real-time engineering simulator is verified using experimental results from a Ballard Nexa fuel cell system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1878-1884
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• 2000

In multibody dynamic analysis, one of the most important problems is to reduce computation times for real time simulation. In this paper, a symbolic computation method is implemented and tested for each dynamic analysis step. Applying symbolic formulations to the vehicle dynamics program AutoDyn7, the effectiveness of the symbolic computation method is verified.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.159-179
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• 2022

Often a network becomes complex, and multiple entities would get in charge of managing part of the whole network. An example is a utility grid. While the entire grid would go under a single utility company's responsibility, the network is often split into multiple subsections. Subsequently, each subsection would be given as the responsibility area to the corresponding sub-organization in the utility company. The issue of how to make subsystems of adequate size and minimum number of interconnections between subsystems becomes more critical, especially in real-time simulations. Because the computation capability limit of a single computation unit, regardless of whether it is a high-speed conventional CPU core or an FPGA computational engine, it comes with a maximum limit that can be completed within a given amount of execution time. The issue becomes worsened in real time simulation, in which the computation needs to be in precise synchronization with the real-world clock. When the subject of the computation allows for a longer execution time, i.e., a larger time step size, a larger portion of the network can be put on a computation unit. This translates into a larger margin of the difference between the worst and the best. In other words, even though the worst (or the largest) computational burden is orders of magnitude larger than the best (or the smallest) computational burden, all the necessary computation can still be completed within the given amount of time. However, the requirement of real-time makes the margin much smaller. In other words, the difference between the worst and the best should be as small as possible in order to ensure the even distribution of the computational load. Besides, data exchange/communication is essential in parallel computation, affecting the overall performance. However, the exchange of data takes time. Therefore, the corresponding consideration needs to be with the computational load distribution among multiple calculation units. If it turns out in a satisfactory way, such distribution will raise the possibility of completing the necessary computation in a given amount of time, which might come down in the level of microsecond order. This paper presents an effective way to split a given electrical network, according to multiple criteria, for the purpose of distributing the entire computational load into a set of even (or close to even) sized computational loads. Based on the proposed system splitting method, heavy computation burdens of large-scale electrical networks can be distributed to multiple calculation units, such as an RTDS real time simulator, achieving either more efficient usage of the calculation units, a reduction of the necessary size of the simulation time step, or both.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.12
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• pp.1433-1441
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• 2009

In multibody dynamic analysis, one of the most important problems is to reduce computation times for real-time simulation. This paper presents the derivation procedure of equations of motion of a 6${\times}$6 autonomous vehicle in terms of chassis local coordinates which do not require coordinates transformation matrix to enhance efficiency for real-time dynamic analysis. Also, equations of motion are derived using the VT(velocity transformation) technique and symbolic computation method coded by MATLAB. The Jacobian matrix of the equations of motion of a system is derived from symbolic operations to apply the implicit integration method. The analysis results were compared with ADAMS results to verify the accuracy and approve the feasibility of real time analysis.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.355-365
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• 2022

This paper addresses the problem of real-time tracking a high-speed ballistic target. Particle filters can be considered to overcome the nonlinearity in motion and measurement models in the ballistic target. However, it is difficult to apply particle filters to real-time systems because particle filters generally require much computation time. This paper proposes an accelerated particle filter using graphics processing unit (GPU) for real-time ballistic target tracking. The real-time performance of the proposed method was tested and analyzed on a widely-used embedded system. The comparison results with the conventional particle filter on CPU (central processing unit) showed that the proposed method improved the real-time performance by reducing computation time significantly.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.127-133
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• 2003

This paper proposes a new numerical method to check the stability of a general class of time delay systems. The proposed method checks whether there are characteristic roots whose real values are nonnegative through two steps. Firstly, rectangular bounds of characteristic roots whose real values are nonnegative are computed. Secondly, the existence of roots inside the bounds are checked using the numerical computation of argument principles. An adaptive discretization is proposed for the numerical computation of argument principles.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.439-445
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• 2007

GVF can solve two difficulties with Snakes that are on setting initial contour and have a hard time processing into boundary concavities. But GVF takes much longer computation time than the existing Snakes because of their edge map and partial derivatives. Therefore this paper analyzed the computation time between GVF and Snakes. As a simulation result, both algorithms took almost similar computation time in simple image. In real images, GVF took about two times computation than Snakes.

• ETRI Journal
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• v.43 no.1
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• pp.82-94
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• 2021

In this work, six voiced/unvoiced speech classifiers based on the autocorrelation function (ACF), average magnitude difference function (AMDF), cepstrum, weighted ACF (WACF), zero crossing rate and energy of the signal (ZCR-E), and neural networks (NNs) have been simulated and implemented in real time using the TMS320C6713 DSP starter kit. These speech classifiers have been integrated into a linear-predictive-coding-based speech analysis-synthesis system and their performance has been compared in terms of the percentage of the voiced/unvoiced classification accuracy, speech quality, and computation time. The results of the percentage of the voiced/unvoiced classification accuracy and speech quality show that the NN-based speech classifier performs better than the ACF-, AMDF-, cepstrum-, WACF- and ZCR-E-based speech classifiers for both clean and noisy environments. The computation time results show that the AMDF-based speech classifier is computationally simple, and thus its computation time is less than that of other speech classifiers, while that of the NN-based speech classifier is greater compared with other classifiers.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.105-109
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• 2001

This paper discuss the real-time self-tuning learning control based on evolutionary computation, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes.