• Proceedings of the KIPE Conference
• /
• 1998.10a
• /
• pp.609-614
• /
• 1998

A new small signal modeling of an average current mode control is proposed. In order to analyze the characteristics of the control scheme, the discrete and continuous time small signal models are derived. The derivation are mainly come from the analysis of the sampling effect presented in the current control loop. By the mathematical interpretation of practical sampler representing the sampling effect of a current control loop, the small signal models of an average current mode control can be easily derived. The instability of the current control loop, which gives rise to the subharmonic oscillation, can be identified by the proposed models. To show the usefulness of the proposed models, the simulation and experiment are carried out. The results show that the predicted results by the proposed model are much better agreed with the measured ones than that of the conventional model, even though the high gain of the compensation network of a current control loop is employed.

• Journal of Power Electronics
• /
• v.12 no.3
• /
• pp.399-409
• /
• 2012

In DC-DC Buck converters with average current mode control, the current loop compensator provides additional design freedom to enhance the converter current loop performance. On the other hand, the current loop circuit elements append substantial amount of complexity to not only the inner current loop but also the outer voltage loop, which makes it demanding to quantify circuit and operating parameter effects on the small-signal dynamics of such converters. Despite the difficulty, it is shown in this paper that parameter effects can be analyzed satisfactorily by using an existing small-signal model in conjunction with a newly proposed simplified alternative. As a result of the study, new insight into average current mode control is uncovered and discussed quantitatively. Measurable experimental results on a prototype averaged-current-mode-controlled Buck converter are provided to facilitate the analytical study with good correlation.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.3 no.4
• /
• pp.338-345
• /
• 1998

The mathematical interpretation of a practical sampler which is useful to obtain the small signal models for the peak and average current mode controls is proposed. Due to the difficulties in applying the Shannons sampling theorem to the analysis of sampling effects embedded in the current mode control, several different approaches have been reported. However, these approaches require the information of the inductor current in a discrete expression, which restricts the application of the reported method only to the peak current mode control. In this paper, the mathematical expressions of sampling effects on a current loop which can directly apply the Shannons sampling theorem are newly proposed, and applied to the modeling of the peak current mode control. By the newly derived models of a practial smapler, the models in a discrete time domain and a continuous time domain are obtained. It is expected that the derived models are useful for the control loop design of power supplies. The effectiveness of the derived models are verified through the simulation and experimental results.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.10 no.4
• /
• pp.347-355
• /
• 2005

In this paper, a new continuous~time small signal model of an average current mode control is proposed. Sampling effect Is considered to obtain the proposed small signal model. By the proposed model, the high frequency response characteristics of current loop gain might be predicted accurately compared to previous models. And this leads the prediction of inductor current response of the proposed model to be accurate compared to others. In order to show the usefulness of the proposed model, prediction results of the proposed model are compared to those of the circuit level simulator, PSIM and experiment.

• Journal of Power Electronics
• /
• v.12 no.3
• /
• pp.410-417
• /
• 2012

In this paper, a direct current control method based on a one-cycle controller (DCOCC) for double frequency buck converters (DF buck) is proposed. This control method can make the average current through the high frequency and low frequency inductors of a DF buck converter equal. This is similar to the average current control method. However, the design of the loop compensator is much easier when compared with the average current control. Since the average current though the high frequency and low frequency inductors is equivalent, the current stress of the high frequency switches and the switch losses are minimized. Therefore, the efficiency of the DF buck converter is improved. Firstly, the operation principle of DCOCC is described, then the small signal models of a one cycle controller and a DF buck converter are presented based on the state space average method. Eventually, a system block diagram of the DCOCC controlled DF buck is established and the compensator is designed. Finally, simulation and experiment results are given to verify the correction of the theory analysis.

• Proceedings of the KIPE Conference
• /
• 1998.07a
• /
• pp.275-278
• /
• 1998

The mathematical interpretation of a practical sampler which is useful to obtain the small signal models for the peak and average current mode controls is proposed. Due to the difficulties in applying the Shannon's sampling theorem to the analysis of sampling effects embedded in the current mode control, several different approaches have been reported. However, these approaches require the information of the inductor current in a discrete expression, which restricts the application of the reported method only to the peak current mode control. In this paper, the mathematical expressions of sampling effects on a current loop which can directly apply the Shannon's sampling theorem are newly proposed, and applied to the modeling of the peak current mode control. By the newly derived models of a practical sampler, the models in a discrete time domain and a continuous time domain are obtained. It is expected that the derived models are useful for the control loop design of power supplies. The effectiveness of the derived models are verified through the simulation and experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.12
• /
• pp.3923-3942
• /
• 2022

Environment, price, regulation, and other factors influence the price of agricultural products, which is a social signal of product supply and demand. The price of many agricultural products fluctuates greatly due to the asymmetry between production and marketing details. Horticultural goods are particularly price sensitive because they cannot be stored for long periods of time. It is very important and helpful to forecast the price of horticultural products which is crucial in designing a cropping plan. The proposed method guides the farmers in agricultural product production and harvesting plans. Farmers can benefit from long-term forecasting since it helps them plan their planting and harvesting schedules. Customers can also profit from daily average price estimates for the short term. This paper study the time series models such as ARIMA, SARIMA, and neural network models such as BPN, LSTM and are used for wheat cost prediction in India. A large scale available data set is collected and tested. The results shows that since ARIMA and SARIMA models are well suited for small-scale, continuous, and periodic data, the BPN and LSTM provide more accurate and faster results for predicting well weekly and monthly trends of price fluctuation.

• Journal of Communications and Networks
• /
• v.12 no.4
• /
• pp.289-307
• /
• 2010

The problem of model selection arises in a number of contexts, such as subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper studies non-asymptotic model selection for the general case of arbitrary (random or deterministic) design matrices and arbitrary nonzero entries of the signal. In this regard, it generalizes the notion of incoherence in the existing literature on model selection and introduces two fundamental measures of coherence-termed as the worst-case coherence and the average coherence-among the columns of a design matrix. It utilizes these two measures of coherence to provide an in-depth analysis of a simple, model-order agnostic one-step thresholding (OST) algorithm for model selection and proves that OST is feasible for exact as well as partial model selection as long as the design matrix obeys an easily verifiable property, which is termed as the coherence property. One of the key insights offered by the ensuing analysis in this regard is that OST can successfully carry out model selection even when methods based on convex optimization such as the lasso fail due to the rank deficiency of the submatrices of the design matrix. In addition, the paper establishes that if the design matrix has reasonably small worst-case and average coherence then OST performs near-optimally when either (i) the energy of any nonzero entry of the signal is close to the average signal energy per nonzero entry or (ii) the signal-to-noise ratio in the measurement system is not too high. Finally, two other key contributions of the paper are that (i) it provides bounds on the average coherence of Gaussian matrices and Gabor frames, and (ii) it extends the results on model selection using OST to low-complexity, model-order agnostic recovery of sparse signals with arbitrary nonzero entries. In particular, this part of the analysis in the paper implies that an Alltop Gabor frame together with OST can successfully carry out model selection and recovery of sparse signals irrespective of the phases of the nonzero entries even if the number of nonzero entries scales almost linearly with the number of rows of the Alltop Gabor frame.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.12 no.7
• /
• pp.1191-1198
• /
• 2001

MMIC low noise amplifiers for millimeter-wave application using 0.15 $\mu$m pHEMT have been presented in this paper. The design emphasis is on active device model and EM simulation. The deficiency of conventional device models is identified. A distributed device model has been adapted to circumvent the scaling problems and, thus, to predict small signal and noise parameters accurately. Two single-ended low noise amplifier are designed using distributed active device model for Q-band(40 ∼ 44 GHz) and V-band(58 ∼65 GHz) application. The Q-band amplifier achieved a average noise figure of 2.2 dB with 18.3 dB average gain. The V-band amplifier achieved a average noise figure of 2.9 dB with 14.7 dB average gain. The design technique and model employed provides good agreement between measured and predicted results. Compared with the published data, this work also represents state-of-the-art performance in terms of gain and noise figure.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.11 no.3
• /
• pp.179-196
• /
• 1986

In this paper, the peformance of a statistical packet voice/data multiplexer is studied. In ths study we assume that in the packet voice/data multiplexer two separate finite queues are used for voice and data traffics, and that voice traffic gets priority over data. For the performance analysis we divide the output link of the multiplexer into a sequence of time slots. The voice signal is modeled as an (M+1) - state Markov process, M being the packet generation period in slots. As for the data traffic, it is modeled by a simple Poisson process. In our discrete time domain analysis, the queueing behavior of voice traffic is little affected by the data traffic since voice signal has priority over data. Therefore, we first analyze the queueing behavior of voice traffic, and then using the result, we study the queueing behavior of data traffic. For the packet voice multiplexer, both inpur state and voice buffer occupancy are formulated by a two-dimensional Markov chain. For the integrated voice/data multiplexer we use a three-dimensional Markov chain that represents the input voice state and the buffer occupancies of voice and data. With these models, the numerical results for the performance have been obtained by the Gauss-Seidel iteration method. The analytical results have been verified by computer simylation. From the results we have found that there exist tradeoffs among the number of voice users, output link capacity, voic queue size and overflow probability for the voice traffic, and also exist tradeoffs among traffic load, data queue size and oveflow probability for the data traffic. Also, there exists a tradeoff between the performance of voice and data traffics for given inpur traffics and link capacity. In addition, it has been found that the average queueing delay of data traffic is longer than the maximum buffer size, when the gain of time assignment speech interpolation(TASI) is more than two and the number of voice users is small.