• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.2
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• pp.399-407
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• 1996

A fuzzy learning algorithm to get the optimal fuzzy rules is presented in this paper. The algorithm introduces a reference model to generate a desired output and a performance index funtion instead of the performance index table. The performance index funtion is a cost function based on the error and error-rate between the reference and plant output. The cost function is minimized by a gradient method and the control input is also updated. In this case, the control rules which generate the desired response can be obtained by changing the portion of the error-rate in the cost funtion. In SISO(Single-Input Single- Output)plant, only by the learning delay, it is possible to experss the plant model and to get the desired control rules. In the long run, this algorithm gives us the good control rules with a minimal amount of prior informaiton about the environment.

• Management & Information Systems Review
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• v.6
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• pp.117-135
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• 2001

This study investigates whether the post-merger bad performance of merging firms was caused by the increase of cost and which cost is responsible for that, if it were. To do this, it is investigated whether there is any difference in terms of cost between pre-merger versus post-merger firms. Also the comparison of cost is used between merging firms and non-merging control groups. The finding is that the merging firms have a bigger cost than the non-merging control group and the post-merger firms have a bigger cost than the pre-merger firms. Especially labor cost to revenue and depreciation cost to revenue are statistically very different among them. Thus it is suggested that there are inefficiency of manpower and assets.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.2
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• pp.140-149
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• 2000

A comparative analysis was peformed on the operation cost at partial loads between ice storage systems with the two conventional control strategies, i.e., storage priority and chiller priority. The storage priority control is shown to be more economic for small cooling loads, while the chiller priority control is superior when the cooling load is as large as the design value. Based on this finding, a new control strategy is devised for an ice-storage system to minimize the operation cost at any cooling load. The new control strategy is found to be comparable to the chiller priority for large cooling loads, while it is more economic for small loads compared to the conventional control strategies. The practicality of the new control strategy is also confirmed through a performance test applying the new control strategy to an existing ice-storage system.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.274-276
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• 2007

In this paper, a low cost and high reliability control scheme is proposed for 400Hz UPS system operated in parallel. The proposed control scheme is consisted of two parts which are synchronization and load sharing control. The synchronization control is achieved by discrete logic ICs and analog circuit. The load sharing control is realized by current transformers (CTs) without any controller. Therefore, This proposed control scheme is rather simple and the cost may be decreased, compared with control scheme using expensive controller such as DSP and CAN. The practical feasibility of the proposed control scheme is proved by analysis and simulation.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.04a
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• pp.387-393
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• 2001

Installing vibration control devices in the structure rises as a solution instead of increasing structural strength considering construction cost. Especially, viscoelastic dampers show excellent vibration control performance at low cost and are easy to install in existing structures compared with other control devices. Therefore, cost-effectiveness of structure with viscoelastic dampers needs to be evaluated. Previous cost-effectiveness evaluation method for the seismically isolated structure(Koh et al., 1999;2000)is applied on the building structure with viscoelastic dampers, which combines optimal design and cost-effectiveness evaluation for seismically isolated structures based on minimum life-cycle cost concept. Input ground motion is modeled in the form of spectral density function to take into account acceleration and site coefficients. Damping of the viscoelastic damper is considered by modal strain energy method. Stiffness of shear building and shear area of viscoelastic damper are adopted as design variables for optimization. For the estimation of failure probability, transfer function of the structure with viscoelastic damper for spectral analysis is derived from the equation of motion. Results reveal that cost-effectiveness of the structure with viscoelastic dampers is relatively high in how seismic region and stiff soil condition.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.699-717
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• 2012

In this paper, we deal with the robust mixed $H_2/H_{\infty}$ guaranteed-cost control problem involving uncertain neutral stochastic distributed delay systems. More precisely, the aim of this problem is to design a robust mixed $H_2/H_{\infty}$ guaranteed-cost controller such that the close-loop system is stochastic mean-square exponentially stable, and an $H_2$ performance measure upper bound is guaranteed, for a prescribed $H_{\infty}$ attenuation level ${\gamma}$. Therefore, the fast convergence can be fulfilled and the proposed controller is more appealing in engineering practice. Based on the Lyapunov-Krasovskii functional theory, new delay-dependent sufficient criteria are proposed to guarantee the existence of a desired robust mixed $H_2/H_{\infty}$ guaranteed cost controller, which are derived in terms of linear matrix inequalities(LMIs). Furthermore, the design problem of the optimal robust mixed $H_2/H_{\infty}$ guaranteed cost controller, which minimized an $H_2$ performance measure upper bound, is transformed into a convex optimization problem with LMIs constraints. Finally, two simulation examples illustrate the design procedure and verify the expected control performance.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.196-203
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• 2003

Recent increase in accessibility to the internet makes it easy to use the internet-connected devices. The internet could allow any user can reach and command any device that is connected to the network. But these teleoperation systems using the internet connected device have several problems such as the network time delay, data loss and development cost of an application for the communication with each other. One feasible solution is to use local and external network line for the network time delay, transmission control protocol for data loss and Java language to reduce the development period and cost. In this study, web-based remote control system using Java language is newly proposed and implemented to a pneumatic servo control system to solve the time delay, data loss and development cost. We have conducted several experiments using pneumatic rodless cylinder through the internet and verified that the proposed remote control system was very effective.

• Corrosion Science and Technology
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• v.9 no.4
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• pp.159-163
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• 2010

Precise coating weight control is very important issue on quality and minimizing operating costs on continuous galvanizing line. These days, many steel making companies are having a new understanding of cost importance by rise raw material prices and customer's requirement for cost reduction. Dongbu steel also meets these situations and decided to develop the technologies. Dongbu Steel developed Integrated coating weight control system jointly with Objective Control Ltd. and installed 2CGL and 4CGL. Several technological functions were developed and realized to achieve true hands-off operation and maximum cost benefit by combining model-based preset and dynamic prediction models. We also installed it on 1 CGL on April, 2008. This paper will present the interface, functions and application result of the integrated coating weight control system including Zn saving and coating weight uniformity.

• Land and Housing Review
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• v.10 no.3
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• pp.9-16
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• 2019

This study aimed at developing control algorithms for operating a variable refrigerant flow (VRF) heating and cooling system with optimal system parameter set-points. Two artificial neural network (ANN) models, which were respectively designed to predict the heating energy cost and cooling energy amount for upcoming next control cycle, was developed and embedded into the control algorithms. Performance of the algorithms were tested using the computer simulation programs - EnergyPlus, BCVTB, MATLAB in an incorporative manner. The results revealed that the proposed control algorithms remarkably saved the heating energy cost by as much as 7.93% and cooling energy consumption by as much as 28.44%, compared to a conventional control strategy. These findings support that the ANN-based predictive control algorithms showed potential for cost- and energy-effectiveness of VRF heating and cooling systems.