• Journal of Power Electronics
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• v.7 no.2
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• pp.174-180
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• 2007

In this paper, a simple control method for two-stage utility grid-connected photovoltaic power conditioning systems (PCS) is proposed. This approach enables maximum power point (MPP) tracking control with post-stage inverter current information instead of calculating solar array power, which significantly simplifies the controller and the sensor. Furthermore, there is no feedback loop in the pre-stage converter to control the solar array voltage or current because the MPP tracker drives the converter switch duty cycle. This simple PCS control strategy can reduce the cost and size, and can be utilized with a low cost digital processor. For verification of the proposed control strategy, a 2.5kW two-stage photovoltaic grid-connected PCS hardware which consists of a boost converter cascaded with a single-phase inverter was built and tested.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.577-587
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• 2023

Conventional categorical data imputation techniques, such as mode imputation, often encounter issues related to overestimation. If the variable has too many categories, multinomial logistic regression imputation method may be impossible due to computational limitations. To rectify these limitations, we propose a two-stage imputation method. During the first stage, we utilize the Boruta variable selection method on the complete dataset to identify significant variables for the target categorical variable. Then, in the second stage, we use the important variables for the target categorical variable for logistic regression to impute missing data in binary variables, polytomous regression to impute missing data in categorical variables, and predictive mean matching to impute missing data in quantitative variables. Through analysis of both asymmetric and non-normal simulated and real data, we demonstrate that the two-stage imputation method outperforms imputation methods lacking variable selection, as evidenced by accuracy measures. During the analysis of real survey data, we also demonstrate that our suggested two-stage imputation method surpasses the current imputation approach in terms of accuracy.

• Smart Structures and Systems
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• v.5 no.1
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• pp.1-21
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• 2009

A two-stage damage detection method is proposed and demonstrated for structural health monitoring. In the first stage, the subset selection method is applied for the identification of the multiple damage locations. In the second stage, the damage severities of the identified damaged elements are determined applying SSGA to solve the optimization problem. In this method, the sensitivities of residual force vectors with respect to damage parameters are employed for the subset selection process. This approach is particularly efficient in detecting multiple damage locations. The SEREP is applied as needed to expand the identified mode shapes while using a limited number of sensors. Uncertainties in the stiffness of the elements are also considered as a source of modeling errors to investigate their effects on the performance of the proposed method in detecting damage in real-life structures. Through a series of illustrative examples, the proposed two-stage damage detection method is demonstrated to be a reliable tool for identifying and quantifying multiple damage locations within diverse structural systems.

• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.65-76
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• 1990

A lot-sizing model for multi-stage MRP systems is proposed, in which known demands must be satisfied. In this model, an approach with considerations of initial inventory and limited production capacity is involved. Most of the studies on the lot-sizing techniques for multi-stage material requirement planning systems have been focused upon two basic approaches. One approach is to develope an algorithm yielding an optimal solution. Due to the computational complexity and sensitivity of the optimal solution to the problem of lot sizing, heuristic approaches are often employed. In this paper, the heuristic approach is used by sequential application of a single-stage algorithm with a set of modified cost by the concept of multi-echelon costs. The proposed method is compared with an lot-sizing method(Florian-Klein Model) to prove its effectiveness by numerical examples.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.2
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• pp.147-153
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• 2017

In order to demonstrate a target reliability with a specified confidence level, a new two-stage Bayesian Reliability Demonstration Test (RDT) plans that is known to be more effective than a corresponding single-stage one is proposed and developed by Bayesian framework with beta prior distribution for Weibull life time distribution. A numerical example is provided to illustrate the proposed RDT plans and compared with other non-Bayesian and Bayesian plans. Comparative results show that the proposed Bayesian two-stage plans have some merits in terms of required and expected testing time and probability of acceptance.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.5
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• pp.845-851
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• 2013

In this paper, a robust optimization approach is applied to the two-axes stage using a piezoelectric actuator for precise motion tracking. Robust control is based on LQG/LTR (linear quadratic Gaussian control with loop transfer recovery) control. Further, an LMI (linear matrix inequality) is used to find the optimal parameter in the loop transfer recovery step, instead of a trial and error method. A decoupler in the shape of FIR filter is added to reduce the coupling effect between the motions of the two axes, and hence, the feedback control loop is designed independently for each axis motion. The experimental result shows that the proposed control scheme can be applied effectively for motion control of the two-axes stage.

• ETRI Journal
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• v.45 no.4
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• pp.690-703
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• 2023

Multistage amplifiers have become appropriate choices for high-speed electronics and data conversion. Because of the large number of high-impedance nodes, frequency compensation has become the biggest challenge in the design of multistage amplifiers. The new compensation technique in this study uses two differential stages to organize feedforward and feedback paths. Five Miller loops and a 500-pF load capacitor are driven by just two tiny compensating capacitors, each with a capacitance of less than 10 pF. The symbolic transfer function is calculated to estimate the circuit dynamics and HSPICE and TSMC 0.18 ㎛. CMOS technology is used to simulate the proposed five-stage amplifier. A straightforward iterative approach is also used to optimize the circuit parameters given a known cost function. According to simulation and mathematical results, the proposed structure has a DC gain of 190 dB, a gain bandwidth product of 15 MHz, a phase margin of 89°, and a power dissipation of 590 ㎼.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.748-753
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• 2005

Among processes to manufacture parts from footwear materials like upper leathers, one of the most essential processes is the cutting one optimally arranging lots of parts on raw footwear materials and cutting. A new nesting strategy was proposed for the 2-dimensional part layout by using a two-stage approach, where which can be effectively used for water jet cutting. In the initial layout stage, a SOAL(Self-Organization Assisted Layout) based on the combination of FCM(Fuzzy C-Means) and SOM was adopted. In the layout improvement stage, SA(Simulated Annealing) based approach was adopted for a finer layout. The proposed approach saves much CPU time through a two-stage approach scheme, while other annealing-based algorithm so far reported fur a nesting problem are computationally expensive. The proposed nesting approach uses the stochastic process, and has a much higher possibility to obtain a global solution than the deterministic searching technique. We developed the automatic nesting software of NST(ver.1.1) software for footwear industry by implementing of these proposed algorithms. The NST software was applied by the optimized automatic arrangement algorithm to cut without the loss of leathers. if possible, after detecting damage areas. Also, NST software can consider about several features in not only natural loathers but artificial ones. Lastly, the NST software can reduce a required time to implement generation of NC code. cutting time, and waste of raw materials because the NST software automatically performs parts arrangement, cutting paths generation and finally NC code generation, which are needed much effect and time to generate them manually.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.5
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• pp.422-430
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• 2014

This study proposes a small-signal model and control design for a two-stage DC-DC-AC converter to investigate its dynamic characteristics in relation to battery energy storage system. When the circuit analysis of the two-stage DC-DC-AC converter is attempted simultaneously, the mathematical procedure of deriving the dynamic equation is complex and difficult. The main idea of modeling the two-stage DC-DC-AC converter states that this topology is separated into a bidirectional DC-DC converter and a single-phase inverter with an equivalent current source corresponding to that of the inverter or converter. The dynamic equations for the separated converter and inverter are then derived using the state-space averaging technique. The procedures of building the small-signal model of the two-stage DC-DC-AC converter are described in detail. Based on the derived small-signal model, the individual controllers are designed through a frequency-domain analysis. The simulation and experimental results verify the validity of the proposed modeling approach and controller design.

• Smart Structures and Systems
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• v.15 no.1
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• pp.57-80
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• 2015

Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.