• Food Science and Preservation
• /
• v.9 no.2
• /
• pp.137-143
• /
• 2002

Temperature and humidity are the most important factors and should be effectively controlled for the cold storage of graius. Fuzzy logic can be easily implemented to the MIMO(Multi-Input Multi-Output) control systems. For the cold storage in grain bin, fuzzy logic was applied to an air conditioning system. The capacities of the grain bin and the air conditioner are 80 tons and 30㎾, respectively. Also, the target values of temperature and relative humidity in outlet duct of the air conditioner were 8$\^{C}$ and 75%, respectively. In order to control temperature and relative humidity of air, a damper in inlet duct was manipulated for temperature control and a heater was used for humidity control. Temperature deviation and change of temperature deviation were used as input parameters for the fuzzy system. Humidity was only considered as a load. The experimental results showed that the controlled temperature of exhausted air was maintained at 8$\pm$2$\^{C}$. Relative humidity of the air was also controlled at the target relative humidity of 50∼80%.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.135-135
• /
• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.6C
• /
• pp.642-648
• /
• 2009

In this paper, we use SA (Seysen's Algorithm) instead of LLL (Lenstra-Lenstra-Lovasz) to perform LRA (Lattice Reduction-Aided) detection. By using SA, the complexity of lattice reduction is reduced and the detection performance is improved Although the performance is improved using SA, there still exists a gap in the performance between SA-LRA and ML detection. To reduce the performance difference, we apply list of candidates scheme to SA-LRA. The list of candidates scheme finds a list of candidates. Then, the candidate with the smallest squared Euclidean distance is considered as the estimate of the transmitted signal. Simulation results show that the SA-LRA detection learn to quasi-ML performance. Moreover, the efficiency of the SA is shown to highly improve the channel matrix conditionality.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.6C
• /
• pp.634-641
• /
• 2009

The goal of OSIC-series detection methods is to approach the ML performance with feasible complexity. However, since they sometimes suffer from the empty vector problem, they can not achieve the soft-output ML performance or many candidate vectors are required to achieve the soft-output ML performance. In this paper, we propose the novel detection method, which can generate the reliable soft-outputs without suffering from empty vector problem. The proposed detector can approach the near soft-output ML performance as well as hard-output. Further, the complexity study shows that the proposed detection method has the lowest complexity compared to the other detectors having the near ML performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.728-731
• /
• 2015

Nowadays, the majority of the manufacturing plant equipment tend to be transformed with automation system than traditional manual equipment. Production manager to make the process decision-making, not accustomed to manage and take advantage of professional decision-making technique. So rather than using the system proposed, it is common to undergo sporadic measures through the external intermediary. In this paper, whether possible delivery to match the delivery through the issue and decision-making system of the data input to be generated in the manufacturing process, review the supply information of the material used in the process, a plurality of input / output device We have proposed an input module that utilizes the Android Application and ATmega2560. As a result, easily cope with the improvement and change of process information of the work efficiency of the production business of the manufacturing process, and reduced plant data missing tasks, and management improvement to the improvement of the delivery compliance and product satisfaction by improving productivity we try to contribute to.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.4C
• /
• pp.414-423
• /
• 2009

This paper considers a linear precoding scheme that achieves near optimal sum rate. While the minimum mean square error (MMSE) precoding provides the better MSE performance at all signal-to-noise ratio (SNR) than the zero forcing (ZF) precoding, its sum rate shows superior performance to ZF precoding at low SNR but inferior performance to ZF precoding at high SNR, From this observation, we first propose a near optimal linear precoding scheme in terms of sum rate. The resulting precoding scheme regularizes ZF precoding to maximize the sum rate, resulting in better sum rate performance than both ZF precoding and MMSE precoding at all SNR ranges. To find regularization parameters, we propose a simple algorithm such that locally maximal sum rate is achieved. As a low complexity alternative, we also propose a simple power re-allocation scheme in the conventional regularized channel inversion scheme. Finally, the proposed scheme is tested under the presence of channel estimation error. By simulation, we show that the proposed scheme can maintain the performance gain in the presence of channel estimation error and is robust to the channel estimation error.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.7C
• /
• pp.618-627
• /
• 2010

In this paper, we propose an adaptive K-best algorithm in which the number K of candidates is changed according to the differences of level radii. We also compare the bit error performance and complexity of the proposed algorithm with those of several conventional K-best algorithms, where the complexity is defined as the total number of candidates of which partial Euclidean distances have to be calculated. The proposed algorithm adaptively decides K at each level by eliminating the symbols, whose differences of radii are larger than a threshold, from the set of candidates, and the maximum or average value of differences can be adopted as the threshold. The proposed decoding algorithm shows the better bit error performance and the lower complexity than a conventional K-best decoding algorithm with a constant K, and also has a similar bit error performance and the lower complexity than other adaptive K-best algorithms.

• ETRI Journal
• /
• v.41 no.5
• /
• pp.637-647
• /
• 2019

Separating highly correlated users can reduce the loss caused by spatial correlation (SC) in multiuser multiple-input multiple-output (MU-MIMO) systems. However, few accurate analyses of the loss caused by SC have been conducted. In this study, we define signal-to-interference-plus-noise ratio (SINR) loss to characterize it in multiuser multiple-input single-output (MU-MISO) systems, and use coefficient of correlation (CoC) to describe the SC between users. A formula is deduced to show the accurate relation between SINR loss and CoC. Based on this relation, we propose a user selection method that utilizes CoC to minimize the average SINR loss of users in massive MU-MISO systems. Simulation results verify the correctness of the relation and show that the proposed user selection method is very effective at reducing the loss caused by SC in massive MU-MISO systems.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.8C
• /
• pp.1040-1046
• /
• 2004

The BLAST-OFDM system is an efficient method for high data rate multimedia transmission in futurewireless communication system. In this paper, a linear preceding mechanism and an efficient antenna-subcarrier assignment algorithm are proposed for the conventional BLAST-OFDM system, in order to utilize the full spatial diversity and the interleaved frequency diversity. By computer simulation, the proposed system has proved to achieve 4-5㏈ gain over the conventional BLAST-OFDM system.

• Journal of Power System Engineering
• /
• v.15 no.1
• /
• pp.78-85
• /
• 2011

In order to design the control system of the magnetic bearing for the high speed 3 phase induction motor, the mathematical modeling was conducted and LQ regulator system was designed. When the plant is controllable and detectable, the nominal stability of LQ regulator could be guaranteed. However, LQ regulator doesn't ensure the robustness of stability and performance for the real system because LQ control is the mathematical optimal theory. In this paper to ensure the robustness of stability and performance for the real system, the control systems are designed by the simulation to the variation system parameters and this method was confirmed as an effective means.