• Journal of Advanced Marine Engineering and Technology
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• v.26 no.2
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• pp.219-225
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• 2002

Parameter tuning methods by Ziegler-Nichols for PID controllers are generally classified into Z-N(1) and Z-N(2). The purpose of this paper is to describe what relations exist between the methods of Z-N(1) and Z-N(2), or how Z-N(1) can be originated from Z-N(2) by analyzing one loop control system composing of P or PI controller and time delay process. In this paper, for the first step to seek mutual relations, the simple formulas of Z-N(2) are transformed into those composing of the same parameters as Z-N(1) which is derived from the analysis of frequency characteristics. Then, the approximation of the actual ultimate frequency is proposed as important premise in the translation between Z-N(1) and (2). Such equalization and approximation brings a simple approximated formula which can explain how Z-N(1) is originated from the Z-N(2) in the form of formula.

• Membrane and Water Treatment
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• v.9 no.2
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• pp.129-136
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• 2018

In this contribution, the control of multivariable reverse osmosis (RO) desalination plant using proportional-integral-derivative (PID) controllers is presented. First, feed-forward compensators are designed using simplified decoupling method and then the PID controllers are tuned for flux (flow-rate) and conductivity (salinity). The tuning of PID controllers is accomplished by minimization of the integral of squared error (ISE). The ISEs are minimized using a recently proposed algorithm named as teacher-learner-based-optimization (TLBO). TLBO algorithm is used due to being simple and being free from algorithm-specific parameters. A comparative analysis is carried out to prove the supremacy of TLBO algorithm over other state-of-art algorithms like particle swarm optimization (PSO), artificial bee colony (ABC) and differential evolution (DE). The simulation results and comparisons show that the purposed method performs better in terms of performance and can successfully be applied for tuning of PID controllers for RO desalination plants.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1053-1056
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• 2004

In this article we have applied Schweizer & Sklars t-norm based similarity measures to classification task. We will compare results to fuzzy similarity measure based classification and show that sometimes better results can be found by using these measures than fuzzy similarity measure. We will also show that classification results are not so sensitive to p values with Schweizer & Sklars measures than when fuzzy similarity is used. This is quite important when one does not have luxury of tuning these kind of parameters but needs good classification results fast.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.3
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• pp.262-268
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• 2010

In this paper, a high power active tunable bandpass filter made of dielectric resonators and varactor diodes is designed using the active capacitance circuit generating negative resistance for tuning cellular TX, RX band. An active capacitance circuit's series feedback circuit using GaAs HFET whose $P_{1dB}$ is 32 dBm is used for compensating the losses from the varactor diodes of the tunable bandpass filter. The tuning elements, the varactor diodes are used as the back-to-back configuration to achieve the high power performance, The designed active capacitance circuit improves the insertion loss characteristics. The designed 2-stage active tunable dielectric bandpass filter at cellular band can cover from 800 MHz to 900 MHz. The insertion losses at 836 MHz and 881.5 MHz with 25 MHz bandwidth are 0.48 dB and 0.39 dB, respectively. The $P_{1dB}$ of the designed bandpass filter at TX and RX band are measured as 19.5 dBm and 23 dBm, respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.4
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• pp.49-55
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• 2004

This paper describes a 1550 nm multichannel source using Quatemary/quatemary multiple quantum well (MQW) InGaAsP/InGaAsP quantum confined Stark effect (QCSE) tuning for dense wavelength division multiplex (DWDM) systems with 140 ㎓ channel spacing and 32 nm channel selection bandwidth.

• Journal of Microbiology and Biotechnology
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• v.17 no.1
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• pp.138-145
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• 2007

Anabaena sensory rhodopsin is a seven transmembrane protein that uses all-trans/13-cis retinal as a chromophore. About 22 residues in the retinal-binding pocket of microbial rhodopsins are conserved and important to control the quality of absorbing light and the function of ion transport or sensory transduction. The absorption maximum is 550 nm in the presence of all-trans retinal at dark. Here, we mutated Pro206 to Glu or Asp, of which the residue is conserved as Asp among all other microbial rhodopsins, and the absorption maximum and pKa of the proton acceptor group were measured by absorption spectroscopy at various pHs. Anabaena rhodopsin was expressed best in Escherichia coli in the absence of extra leader sequence when exogenous all-trans retinal was added. The wild-type Anabaena rhodopsin showed small absorption maximum changes between pH4 and 11. In addition, Pro206Asp showed 46 nm blue-shift at pH7.0. Pro206Glu or Asp may change the contribution to the electron distribution of the retinal that is involved in the major role of color tuning for this pigment. The critical residue Ser86 (Asp 96 position in bacteriorhodopsin: proton donor) for the pumping activity was replaced with Asp, but it did not change the proton pumping activity of Anabaena rhodopsin.

• Journal of IKEEE
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• v.28 no.2
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• pp.136-144
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• 2024

In this paper, we propose a PID controller for altitude control of quadrotor system with experimental analysis. The Routh-Hurwitz test is applied to analyze the system to which our proposed controller is applied. We also summarize experimental data in which the gain values of kP, kI, and kD are changed using MATLAB and Simulink based on mathematical modeling of the quadrotor system. Based on the summarized experimental data, we analyze the effect of changes in each gain values (k_P, k_I, k_D) of PID controller on altitude control of quadrotor, and present an algorithm for tuning the PID controller gain values. The PID controller with the proposed algorithm is applied to AR.Drone system, subsequently and result are verifised through experiments.

• Journal of Powder Materials
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• v.31 no.3
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• pp.226-235
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• 2024

InP quantum dots (QDs) have attracted researchers' interest due to their applicability in quantum dot light-emitting displays (QLED) or biomarkers for detecting cancers or viruses. The surface or interface control of InP QD core/ shell has substantially increased quantum efficiency, with a quantum yield of 100% reached by introducing HF to inhibit oxide generation. In this study, we focused on the control of bandgap energy of quantum dots by changing the Zn/(In+Zn) ratio in the In(Zn)P core. Zinc incorporation can change the photoluminescent light colors of green, yellow, orange, and red. Diluting a solution of as-synthesized QDs by more than 100 times did not show any quenching effects by the Förster resonance energy transfer phenomenon between neighboring QDs.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.141-149
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• 2006

In this paper, we introduce an improved algorithm for computing matrix triple product that commonly arises in primal-dual optimization method. In computing $P=AHA^{t}$, we devise a single pass algorithm that exploits the block diagonal structure of the matrix H. This one-phase scheme requires fewer floating point operations and roughly half the memory of the generic two-phase algorithm, where the product is computed in two steps, computing first $Q=HA^{t}$ and then P=AQ. The one-phase scheme achieved speed-up of 2.04 on Intel Itanium II platform over the two-phase scheme. Based on memory latency and modeled cache miss rates, the performance improvement was evaluated through performance modeling. Our research has impact on performance tuning study of complex sparse matrix operations, while most of the previous work focused on performance tuning of basic operations.

• Geomechanics and Engineering
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• v.38 no.5
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• pp.517-528
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• 2024

For numerous tunnelling projects implemented in urban areas due to limited space, it is crucial to take into account the interaction between the foundation, ground, and tunnel. In predicting the deformation of piled foundations and the ground during twin tunnel excavation, it is essential to consider various factors. Therefore, this study derived a prediction model for pile group settlement using machine learning to analyze the importance of various factors that determine the settlement of piled foundations during twin tunnelling. Laboratory model tests and numerical analysis were utilized as input data for machine learning. The influence of each independent variable on the prediction model was analyzed. Machine learning techniques such as data preprocessing, feature engineering, and hyperparameter tuning were used to improve the performance of the prediction model. Machine learning models, employing Random Forest (RF), eXtreme Gradient Boosting (XGB), and Light Gradient Boosting Machine (LightGBM, LGB) algorithms, demonstrate enhanced performance after hyperparameter tuning, particularly with LGB achieving an R² of 0.9782 and RMSE value of 0.0314. The feature importance in the prediction models was analyzed and P_N was the highest at 65.04% for RF, 64.81% for XGB, and P_CTC (distance between the center of piles) was the highest at 31.32% for LGB. SHAP was utilized for analyzing the impact of each variable. P_N (the number of piles) consistently exerted the most influence on the prediction of pile group settlement across all models. The results from both laboratory model tests and numerical analysis revealed a reduction in ground displacement with varying pillar spacing in twin tunnels. However, upon further investigation through machine learning with additional variables, it was found that the number of piles has the most significant impact on ground displacement. Nevertheless, as this study is based on laboratory model testing, further research considering real field conditions is necessary. This study contributes to a better understanding of the complex interactions inherent in twin tunnelling projects and provides a reliable tool for predicting pile group settlement in such scenarios.