• ETRI Journal
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• v.30 no.1
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• pp.81-88
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• 2008

The security threat posed by worms has steadily increased in recent years. This paper discusses the application of the optimal and sub-optimal Internet worm control via Pontryagin's maximum principle. To this end, a control variable representing the optimal treatment strategy for infectious hosts is introduced into the two-factor worm model. The numerical optimal control laws are implemented by the multiple shooting method and the sub-optimal solution is computed using genetic algorithms. Simulation results demonstrate the effectiveness of the proposed optimal and sub-optimal strategies. It also provides a theoretical interpretation of the practical experience that the maximum implementation of treatment in the early stage is critically important in controlling outbreaks of Internet worms. Furthermore, our results show that the proposed sub-optimal control can lead to performance close to the optimal control, but with much simpler strategies for long periods of time in practical use.

• Structural Engineering and Mechanics
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• v.86 no.2
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• pp.197-209
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• 2023

In the case of designing control devices in a building, reliance on experimental formulation or engineering concepts without using optimization algorithms leads to non-optimal solutions or design parameters, which makes the use of control devices costly and unreasonable. The optimization algorithms are capable of identifying the required number of parameters for a specific design problem, however, this process is difficult and inefficient in dealing with some specific optimal design processes. This paper aims to introduce an upgraded version of the salp swarm algorithm to handle some engineering design. The performance of the new upgraded algorithm is tested using some benchmark test functions as well as a six-story benchmark building equipped with semi-active MR dampers. The simulation results show that the proposed algorithm can be successfully applied to get an optimal design of the MR dampers in the building.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.2
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• pp.70-77
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• 2010

In order to improve the efficiency of a main transformer in a train, the optimal operation of a cooling system is necessary. For the development of optimal control algorithms of a cooling system, mathematical models of a main transformer cooling system were developed. These include static and dynamic models of a main transformer, an oil pump, an oil cooler, and a blower. Static models were used to find optimal oil temperatures of the inlet and the outlet of a transformer. Dynamic models were used to predict transient performances of control algorithms of a blower and an oil pump. Simulation results showed good predictions of the static and the dynamic behavior of a main transformer cooling system. Therefore, mathematical models developed in this study may be effectively used for the development of control algorithms of a main transformer cooling system.

• Journal of KSNVE
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• v.11 no.1
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• pp.147-155
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• 2001

This paper is concerned with the real-time automatic tuning of the multi-input multi-output positive position feedback controllers for smart structures by the genetic algorithms. The genetic algorithms have proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The previous real-time algorithm that tunes a single control parameter is extended to tune more parameters of the MIMO PPF controller. We employ the MIMO PPF controller since it can enhance the damping value of a target mode without affecting other modes if tuned properly. Hence, the traditional positive position feedback controller can be used in adaptive fashion in real time. The final form of the MIMO PPF controller results in the centralized control, thus it involves many parameters. The bounds of the control Parameters are estimated from the theoretical model to guarantee the stability. As in the previous research, the digital MIMO PPF control law is downloaded to the DSP chip and a main program, which runs genetic algorithms in real time, updates the parameters of the controller in real time. The experimental frequency response results show that the MIMO PPF controller tuned by GA gives better performance than the theoretically designed PPF. The time response also shows that the GA tuned MIMO PPF controller can suppress vibrations very well.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.4
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• pp.84-90
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• 2011

In active noise control filter, LMS algorithms which used for control filter, assure the convergence property, and computational burden of these algorithms are proportionate to the filter taps. The convergence speed of LMS algorithms is mainly determined by value of the convergence coefficient, so optimal selection of the value of convergence coefficient is very important. In this paper, We proposed novel adaptive fuzzy logic LMS algorithms with FIR filter structure which has better convergence speed and less computational burden than conventional LMS algorithms, for single channel active noise control with ill conditioned signal case. Computer simulations were performed to show the effectiveness of a proposed algorithms.

• International Journal of Automotive Technology
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• v.7 no.4
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• pp.469-475
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• 2006

In this paper, an optimal suspension system with preview of the road input is synthesized for a half tracked vehicle. The main goal of this research is to improve the ride comfort characteristics of a fast moving tracked vehicle in order to maintain the driver's driving capability. Several different kinds of preview control algorithms are evaluated with active or semi-active suspension systems. The road information estimated from the motion of the 1st road-wheel is adequate to make the best use of the preview control algorithm for tracked vehicles. The ride-comfort characteristics of the tracked vehicle are more dependent on pitching angular acceleration than heaving acceleration. The pitching motion is reduced by the suspension system with hard outer suspensions and soft inner suspensions. Simulation results show that the performance of sky-hook algorithms for ride comfort nearly follow that of full state feedback algorithms.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.11
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• pp.599-609
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.11
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• pp.994-1003
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• 2000

Control algorithms for the absorption air conditioning system may be developed by suing dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help the development of effective control algorithms for the system. In this study, a dynamic simulation program for the absorption air conditioning system was developed. Dynamic models for an absorption chiller, a cooling tower, an air handling unit, a boiler, a three way valve, a controller, and a duct were developed and programed. Control algorithms for the absorption chiller, the cooling tower, and the air handling unit were selected, and analyzed to show the effectiveness of dynamic models. From the simulation results, it may be concluded that this simulation program may be effectively used for the development of optimal control algorithms of the absorption air conditioning system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.5
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• pp.348-356
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• 2003

Active vibration control algorithms for the compensator and proto-type testing system have been developed for the suppression of vibrations from the reciprocating engines. At first, the developed algorithm determines optimal control vibration phases by detecting vibration responses of the engine without and with compensator, and then performs the continuous optimal control functions by tracking the change of the vibration frequency and phase. This algorithm is comparatively simple. robust for the external excitations and needless of supplementary operation since the control process is serially carried out. To validate the performance of compensator and algorithm, testing system including excitation device are constructed and tested, and the reductions of vibration levels are observed over than 80 % of the uncontrolled levels at various frequency ranges.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.140-145
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• 2001

Various control algorithms are available to suppress the vibration of a system subjected to disturbances. LQ algorithm is simple and easy to implement the hardwares, but it lacks robustness for uncertainties and often causes difficulty in determining the weighting matrices. This study focuses on the effectiveness ILQ(Inverse Linear Quadratic optimal control) algorithm as the alternative to LQ applied to control the vibration of a building under the seismic excitation. The building is of moment resisting steel frames and assumed to behave within the elastic range. The brief overview of LQ and ILQ algorithms is introduced, and the displacement responses of the structure using ILQ algorithm are compared with those obtained from LQ control. The magnitude of control forces are also determined and compared for both LQ and ILQ algorithm.