• Journal of Ocean Engineering and Technology
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• v.19 no.3
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• pp.66-73
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• 2005

The sway motion control problem of a container hanging on the trolley is considered in this paper. In the container crane control problem, the main issue involves suppressing the residual swing motion of the container at the end of acceleration, during deceleration, or for an unexpected disturbance input. For this problem, in general, many trolley motion control strategies are introduced and applied. In this paper, we introduce and synthesize a swing motion control system, in which a small auxiliary mass is installed on the spreader. In this control system, the actuator reacting against the auxiliary mass applies inertial control forces to the container to reduce the swing motion in the desired manner. In many studies, the controllers used to suppress the vibration have been synthesized for the given mathematical model of plants. In many cases, the designers have not been able to utilize the degree of freedom to adjust the structural parameters for the control object. To overcome this problem, so called "Structure/Control Simultaneous Method" is used. From this, in this paper the simultaneous design method is used to achieve optimal system performance. And the experimental result shows that the proposed control strategy is useful, to the case of that the controlled system is exposed to the uncertainties and, robust to disturbances like wind.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.8
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• pp.33-39
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• 2005

The maximum output torque and power developed by the machine is ultimately depended on the allowable inverter current rating and maximum voltage which the inverter can supply to the machine. Therefore, considering the limited voltage and current capacities, it is desirable to consider a control method which yields the best possible torque per ampere. In this paper, we propose fuzzy neural network(FNN) controller that combines a fuzzy control and the neural network for high performance control of induction motor drive. This controller composes antecedence of the fuzzy rules and consequence by a clustering method and a multi-layer neural networks. This controller is compounding of advantages that robust control of a fuzzy control and high-adaptive control of the neural networks. Also, this paper is proposed control of maximum torque per ampere(MTPA) of induction moor. This strategy is reposed which is simple in structure and has the honest goal of minimizing the stator current magnitude for given load torque. The performance of the proposed induction motor drive with maximum torque control using FNN controller is verified by analysis results at dynamic operation conditions.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.2
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• pp.39-47
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• 1998

It has been known that variable structure control(VSC) has theoretically powerful control technique of providing fast response, no overshoot, and very robust control with respect to system parameter variations and disturbances. However, the technique has not become more widely extended in the industrial circles because chattering phenomenon which may excite high-frequency unmodelled plant dynamics and damage to system components exists. In this paper, a modified variable structure control(MVSC) is developed to alleviate these problems which are applied to the position control of induction motor. While the conventional VSC makes the structure of the system change with high-frequency switching on the center of the one switching surface, in the MVSC two switching surface are used to establish a sliding sector. The structure of the system will be changed with low-frequency switching. Therefore, the proposed algorithm has the properties of reducing chattering, retaining the benefits achieved in the conventional VSC, and working even under the influences of parameter variations. Experimental results show the effectiveness of the control strategy proposed here for the position control of induction motor.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.426-426
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• 1999

;There are many sources of uncertainty in a typical production and inventory system. There is uncertainty as to how many items customers will demand during the next day, week, month, or year. There is uncertainty about delivery times of the product. Uncertainty exacts a toll from management in a variety of ways. A spurt in a demand or a delay in production may lead to stockouts, with the potential for lost revenue and customer dissatisfaction. Firms typically hold inventory to provide protection against uncertainty. A cushion of inventory on hand allows management to face unexpected demands or delays in delivery with a reduced chance of incurring a stockout. The proposed strategies are used for the design of a probabilistic inventory system. In the traditional approach to the design of an inventory system, the goal is to find the best setting of various inventory control policy parameters such as the re-order level, review period, order quantity, etc. which would minimize the total inventory cost. The goals of the analysis need to be defined, so that robustness becomes an important design criterion. Moreover, one has to conceptualize and identify appropriate noise variables. There are two main goals for the inventory policy design. One is to minimize the average inventory cost and the stockouts. The other is to the variability for the average inventory cost and the stockouts The total average inventory cost is the sum of three components: the ordering cost, the holding cost, and the shortage costs. The shortage costs include the cost of the lost sales, cost of loss of goodwill, cost of customer dissatisfaction, etc. The noise factors for this design problem are identified to be: the mean demand rate and the mean lead time. Both the demand and the lead time are assumed to be normal random variables. Thus robustness for this inventory system is interpreted as insensitivity of the average inventory cost and the stockout to uncontrollable fluctuations in the mean demand rate and mean lead time. To make this inventory system for robustness, the concept of utility theory will be used. Utility theory is an analytical method for making a decision concerning an action to take, given a set of multiple criteria upon which the decision is to be based. Utility theory is appropriate for design having different scale such as demand rate and lead time since utility theory represents different scale across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. Using utility theory, three design strategies, such as distance strategy, response strategy, and priority-based strategy. for the robust inventory system will be developed.loped.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.5
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• pp.352-360
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• 2010

This paper proposes a precise position control of an automatic door using a disturbance observer. Although the conventional PID controller is usually used for an automatic door system, the demand of the robust controller considering the parameter deviations and disturbances is increasing due to the various size and weight of a door. The linear model for an automatic door system is presented. Based on this model, the LQR controller using a state feedback controller and an observer are suggested. A disturbance observer to compensate the undesirable factors is also proposed. Simulation and Experimental results are presented to illustrate the feasibility of the proposed control strategy.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.2
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• pp.164-170
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• 2002

Sliding mode control, as a typical method of variable structure control, has the robust characteristics for the uncertainty and the disturbance of the nonlinear system. Because, however, sliding mode control input includes a sign function that Is discontinuous on the predefined switching surface, its applications are primarily limited by the need of alleviation or reduction of chattering. In this paper, we propose a chattering alleviation strategy based on a special nonlinear function and a fuzzy system. By using the proposed control scheme, we can reduce the steady state error. Its tracking performance is as fast as that of conventional method using the fixed boundary layer. Especially, in the proposed method, we can adjust the trade-off between the steady state error and the degree of chattering by regulating the proper range of the output variable of the fuzzy system. To verify the validity of the proposed algorithm, the analysis of the control method using the fixed boundary layer and the computer simulations are shown to compare with them.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2499-2504
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• 2013

Applications of dynamic position control are especially focused on cancellation of unknown disturbance against nonlinear dynamic plants. Control performance is technically dependent upon observation methodology of such disturbance signals. This paper presents a novel control strategy by using linear actuators based on CAN communication networks. Disturbance is measured from placing a ball on a flat plant and image processing technique is applied to observe dynamic position of a ball system. We devise a neural network based PI control system to realize robust control of the dynamic system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1234-1243
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• 1992

A systematic procedure to design fuzzy PID controllers is developed in this paper. The concept of local fuzzy control cell is proposed by introducing both an adequate global control rule and membership functions to simplify a fuzzy logic controller. Fuzzy decision is made by using algebraic product and parallel firing arithematic mean, and a defuzzification strategy is adopted for improving the computational efficiency based on nonfuzzy micro-processor. A direct method, transforming the typical output of quasi-linear fuzzy operator to the digital compensator of PID form, is also proposed. Finally, the proposed algorithm is applied to an DC-servo motor. It is found that this algorithm is systematic and robust through computer simulations and implementation of controller using Intel 8097 micro-processor.

• Journal of Navigation and Port Research
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• v.29 no.8 s.104
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• pp.747-753
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• 2005

In this paper, as an anti-sway control strategy of container cranes, we investigate a variable structure control in which the moving load follows a given trajectory, whereas both the trolley and hoist controllers achieve their positioning problems. It is crucial, in an automated container terminal, that collisions should be avoided during the transference of containers from one place to another. It is also necessary, in the case of a quay crane, to select suitable loading and unloading trajectories of containers, so that possible collisions with surrounding obstacles are avoided. After a brief introduction of the mathematical model, a robust control scheme (i.e., a second-order sliding mode control that guarantees a fast and precise transference and a suppression of the resulted swing) is presented. Despite model uncertainties and unmodeled actuators dynamics, the swing suppression from the given trajectory is obtained by constraining the system motion on suitable sliding surfaces, which include both the desired path and the swing angle. The proposed controller has been tested with a laboratory-size pilot crane. Experimental results are provided.

• The Korean Journal of Franchise Management
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• v.13 no.4
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• pp.39-48
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• 2022

Purpose: COVID-19 has negatively influenced the financial performance of restaurant firms. Previous literature suggests that the franchising strategy effectively helps restaurant firms recover from difficult business conditions through various methods for expanding business size and enhancing business efficiency. According to risk-sharing theory, restaurant franchisors may minimize operational risks by sharing the risks with their franchisees. For instance, restaurant franchisors could generate more stable cash flow using franchise fees from their franchisees. However, research on the effect of franchise's risk reduction factor on business performance during pandemic is scarce. Thus, this study aims to examine the positive moderating effect of franchising between COVID-19 and restaurants' financial performance. Research design, data, and methodology: Panel data including financial information and franchising status of restaurant firms were collected for analysis. In order to control for unobserved firm-specific factors, generalized least squared estimation in fixed effects model was conducted. Huber-White robust standard errors were used to deal with heteroscedasticity issues. Results: It was found that COVID-19 pandemic has a negative effect on the restaurants' financial performance such as ROA (return on assets), ROE (return on equity), and PM (profit margins), which confirms the findings from existing literature. More importantly, results show that the degree of franchising has a positive moderating effect on the relationship between COVID-19 and financial performance of restaurant firms. This suggests that more active engagement in franchising may decrease negative impacts of COVID-19 on the restaurants' financial performance. Conclusions: The study supports existing literature related to risk-sharing theory, by confirming that pandemics, such as COVID-19, negatively affect financial performance of the restaurants. Furthermore, it was found that franchising strategy can help lessen negative impacts of pandemics on the firm performance. These findings can contribute to the franchise and restaurant management literature by suggesting the role of franchising in reducing business risks, thereby positively affecting financial performance. Moreover, this study offers business managers of franchisors and franchisees insights for utilizing franchising in restaurant risk management. Policymakers may also gain information on aiding restaurant firms during global crisis, such as COVID-19.