• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.112-119
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• 2003

Generally, PID controller is not suitable to control multi variable system because it is very difficult to tune the PID gains. However, this paper shows that it is not hard to tune the PID gains if we can find a Jacobian matrix of the system. The Jacobian matrix expresses the ratio of output variations according to input variations. It is possible to adjust the input values in order to reduce the output error using the Jacobian. When the colt function is composed of error related terms, the gradient approach can tune the PID gains to minimize the function. In simulation, a hydrofoil catamaran with two inputs and two outputs is applied as a multi variable system. We can easily get the multi variable PID controller by the proposed teaming method. When the controller is compared with LQR controller, the performance is as good as that of LQR controller with a modeling equation.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.321-325
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• 1986

A new control scheme for the state space model of the robot system using the theory of optimal multi-variable structure is presented in this paper. It is proposed to optimize multi-dimensional variable structure systems for obtaining the required stabilizing signal by minimizing a performance index with respect to the state vector in the sliding mode. It is concluded the proposed variable structure controller yields better system dynamic performance than that obtained by using the only linear optimal controller inthat responses for a step disturbance have a shorter setting time, no matter what overshoot values and rising time.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.342-344
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• 2006

The modem enormous electric power system has made power system analysis much more complex and difficult. For effective analysis of the power system, model reduction and aggregation is required. In this paper, a new aggregation method is presented to aggregate the coherent generators in the large scale power system while matching the power flow. In order to demonstrate the effects of this aggregation method, it is applied to a small scale power system. A multi-variable control technique of $H_{\infty}$ control is also applied to enhance the dynamic stability of the aggregated power system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.12
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• pp.782-790
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• 2011

Typical temperature control methods of a cooler for machine tools are hot-gas bypass and compressor variable speed control. The hot-gas bypass system has been widely used to control the cooler temperature in many general industrial fields. On the contrary, the compressor variable speed control is focused on special fields such as aerospace and high precision machine tools which need high precision control. The variable speed control system usually has two control variables such as target temperature and superheat. In other words, the variable speed control system is basically multi-input multi-output(MIMO) system. In spite of MIMO system, the proportional integral derivative(PID) feedback control methodology that based on single-input single-output (SISO) system is generally used for designing the variable speed control system. Therefore, it is inevitable to describe transfer functions for dynamic behaviors of every controlled variables and decide the PID gains with tremendous iteration process. Moreover, the designed PID gains do not provide optimum system performances. To solve these problems, high performance controller design method based on a state space model is suggested in this paper. An optimum controller is designed to minimize both control errors and energy inputs. This method was more simple to describe dynamic behaviors and easier to design the cooler controller which is MIMO system.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.144-150
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• 1999

n active control for the swing of crane systems is very important for increasing the productivity. This article introduces the control for the position and the swing of a crane using the fuzzy learning method. Because the crane is a multi-variable system, learning is done to control both position and swing of the crane. Also the fuzzy control rules are separately acquired with the loading and unloading situation of the crane for more accurate control. The result of simulations shows that the crane is just controlled for a very large swing angle of 1 radian within nearly one cycle.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.950-960
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• 2010

In this paper, a multi-input multi-output(MIMO) integral variable structure system with an integral-augmented sliding surface is designed for the improved robust control of uncertain multivariable system under the matched persistent disturbance. To effectively remove the reaching phase problems, the integral augmented sliding surface is proposed. Then for its design, the eigenstructure assignment technique is introduced to. To guarantee the designed performance against the persistent disturbance, the stabilizing control for multi-input system is also designed to generate the sliding mode on the integral sliding surface. The stability of the global system together with the existence condition of the sliding mode are investigated and proved for the case of multi input system in the presence of uncertainty and disturbance. The reaching phase is completely removed in proposed MIMO VSS by satisfying the two requirements. An example and computer simulations will be present for showing the usefulness of algorithm.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.8
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• pp.443-449
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• 2013

The purpose of this study is to propose an enhanced variable-speed control method of ground-water circulation pumps using inlet and outlet ground-water temperature difference and analyze its effect for the ground source multi-heat pump system installed in a single-family house. As a result, it has shown to significantly reduce the electricity use of ground-water circulation pump and improve overall system Coefficient of Performance (COP) due to the proposed variable-speed control under partial load conditions after oversized and inefficient single-speed pump retrofit.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.450-453
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• 1997

An active control for the swing of crane systems is very important for increasing the productivity. This article introduces the control for the position and the swing of a crane using the fuzzy learning method. Because the crane is a multi-variable system, learning is done to control both position and swing of the crane. Also the fuzzy control rules are separately acquired with the loading and unloading situation of the crane for more accurate control. The result of simulations shows that the crane is just controlled for a very large swing angle of 1 radian within nearly one cycle.

• 한국신재생에너지학회:학술대회논문집
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• 2005.11a
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• pp.541-544
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• 2005

This study presents the integrated modeling approach to simulate the proton exchange membrane (PEM) fuel cell system for vehicle application. The fuel cell system consisting of stack and balance of plant (BOP) was simulated with MATLAB/Simulink environment to estimate the maximum system power and investigate the effect of BOP component sizing on system performance and efficiency. The PEM fuel cell stack model was established by using a semi-empirical modeling. To maximize the net efficiency of fuel cel1 system, multi-variable optimization code was adopted. Using this method the optimized operating values were obtained according to various system net power levels. The fuel cell model established was co-linked to AVL CRUISE, a vehicle simulation package. Through the vehicle simulation software, the fuel economy of fuel cell powered electric vehicle for two types of driving cycles was presented and compared. It is expected that this study tan be effectively employed in the basic BOP component sizing and in establishing system operation map with respect to net power level of fuel cell system.

• New & Renewable Energy
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• v.1 no.4 s.4
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• pp.43-48
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• 2005

This study presents the integrated modeling approach to simulate the proton exchange membrane [PEM] fuel cell system for vehicle application. The fuel cell system consisting of stack and balance of plant (BOP) was simulated with MATLAB/Simulink environment to estimate the maximum system power and investigate the effect of BOP component sizing on system performance and efficiency. The PEM fuel cell stack model was established by using a semi-empirical modeling. To maximize the net efficiency of fuel cell system, multi-variable optimization code was adopted. Using this method, the optimized operating values were obtained according to various system net power levels. The fuel cell model established was co-linked to AVL CRUISE, a vehicle simulation package. Through the vehicle simulation software, the fuel economy of fuel cell powered electric vehicle for two types of driving cycles was presented and compared. It is expected that this study can be effectively employed in the basic BOP component sizing and in establishing system operation map with respect to net power level of fuel cell system.