• Journal of Mechanical Science and Technology
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• v.19 no.2
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• pp.505-519
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• 2005

In this paper, we develop an anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2 DOF PID controller. The simulation and experimental results show that the proposed control scheme guarantees performances, trolley position, sway angle and settling time in NNP PID controller than other controller. As the results in this paper, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard. Accordingly, the proposed algorithm in this study can be readily used for industrial applications.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.302-307
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• 2001

This research is concerned with the development of a real-time adaptive PPF controller for the active vibration suppression of smart structure. In general, the tuning of the PPF controller is carried out off-line. In this research, the real-time learning algorithm is developed to find the optimal filter frequency of the PPF controller in real time and the efficacy of the algorithm is proved by implementing it in real time. To this end, the adaptive algorithm is developed by applying the gradient descent method to the predefined performance index, which is similar to the method used popularly in the optimization and neural network controller design. The experiment was carried out to verify the validity of the adaptive PPF controller developed in this research. The experimental results showed that adaptive PPF controller is effective for active vibration control of the structure which is excited by either impact or harmonic disturbance. The filter frequency of the PPF controller can be tuned in a very short period of time thus proving the efficiency of the adaptive PPF controller.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1029-1037
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• 2010

If an internal combustion engine is operated by consolidated control, the minimum fuel consumption is achieved and the demanded objectives are satisfied. For this, it is necessary that the engine is operated on the ideal operating line which satisfies minimum fuel consumption. In this context of view, there are many tries to achieve given object. However, the parameters in the internal combustion engines are variable and depend on the operating points. Therefore, it is necessary to cope with the uncertainties such that the optimal operating may be possible. From this point of view, this paper gives a controller design method and a robust stability condition for engine torque control which satisfies the given control performance and robust stability in the presence of physical parameter perturbation. Exactly, in this paper, we consider the robust stability problem of this 2DOF servosystem with nonlinear type uncertainty in the engine system, and a robust stability condition for the servosystem is shown. This result guarantees that if the plant uncertainty is in the permissible set defined by the given condition, then a gain tuning can be carried out to suppress the influence of the plant uncertainties.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.25-32
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• 2007

In this paper, a new method for first order plus dead time(FOPDT) model identification is proposed, which can identity multiple points on a process step response in terms of classification of time response. The process input and output to the test are decomposed into the transient part and the steady-state part. The steady-state part express one FOPDT model and the transient part express variously FOPDT model using least square estimation method. The optimum parameter tuning algorithm for PID controller of the Smith Predictor is proposed through ITAE as performance index. The Simulation results show the validity and improvement of performance for various processes.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.201-203
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• 2007

The paper concerns the successive optimization for structure and parameters of fuzzy inference systems that is based on parallel Genetic Algorithms (PGA) and information data granulation (IG). PGA is multi, population based genetic algorithms, and it is used tu optimize structure and parameters of fuzzy model simultaneously, The granulation is realized with the aid of the C-means clustering. The concept of information granulation was applied to the fuzzy model in order to enhance the abilities of structural optimization. By doing that, we divide the input space to form the premise part of the fuzzy rules and the consequence part of each fuzzy rule is newly' organized based on center points of data group extracted by the C-Means clustering, It concerns the fuzzy model related parameters such as the number of input variables to be used in fuzzy model. a collection of specific subset of input variables, the number of membership functions according to used variables, and the polynomial type of the consequence part of fuzzy rules, The simultaneous optimization mechanism is explored. It can find optimal values related to structure and parameter of fuzzy model via PGA, the C-means clustering and standard least square method at once. A comparative analysis demonstrates that the Dnmosed algorithm is superior to the conventional methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.485-490
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• 2003

RP(Rapid Prototyping) has been used in the various industrial applications. This paper presents the optimization techniques fur fabricated 3D model design using RP machine for the medical field. Once the original brain model data are obtained from 2D slices of MRI/CT machine, the data can be modeled as an optimal ellipse. The objective of this study includes optimization of fabrication time and surface roughness using the adaptive slicing method. It can reduce fabrication time without losing surface roughness quality by accumulating the slices with variable thickness. According to the parameter tuning and synthesis of its effect, more suitable parameter values can be obtained by enhanced 3D brain model fabrication. Therefore, accurate 3D brain model fabricated by RP machine can enable a surgeon to perform pre-operation. to make a decision for the operation sequence and to perceive the 3D positions in prototype, before delicate operation of actual surgery.

• Aerospace Engineering and Technology
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• v.5 no.2
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• pp.195-204
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• 2006

A linear acoustic analysis has been performed to elucidate damping characteristics of acoustic cavities in a liquid rocket combustor. Results have shown that resonant frequencies of acoustic cavity obtained by classical theoretic approach and by the present linear analysis are somewhat different with each other. This difference is attributed to the limitation of the simplified classical theory. To quantify the damping characteristics, acoustic impedance has been introduced and resultant absorption coefficient and conductance have been evaluated. Satisfactory agreement has been achieved with previous experiment. Finally the design procedure for an optimal tuning of acoustic cavity has been established.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1008-1027
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• 2014

An electric scooter with a V-belt continuously variable transmission (CVT) driven by a permanent magnet synchronous motor (PMSM) has a lot of nonlinear and time-varying characteristics, and accurate dynamic models are difficult to establish for linear controller designs. A PMSM servo-drive electric scooter controlled by a novel hybrid modified recurrent Legendre neural network (NN) control system is proposed to solve difficulties of linear controllers under the occurrence of nonlinear load disturbances and parameters variations. Firstly, the system structure of a V-belt CVT driven electric scooter using a PMSM servo drive is established. Secondly, the novel hybrid modified recurrent Legendre NN control system, which consists of an inspector control, a modified recurrent Legendre NN control with an adaptation law, and a recouped control with an estimation law, is proposed to improve its performance. Moreover, the on-line parameter tuning method of the modified recurrent Legendre NN is derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, two optimal learning rates for the modified recurrent Legendre NN are derived to speed up the parameter convergence. Finally, comparative studies are carried out to show the effectiveness of the proposed control scheme through experimental results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.5
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• pp.241-248
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• 2000

Until now, all of the port goods are transported manually by container transporter in the port. Recently there are a lot of studies about unmanned vehicle driven automatically. In terms of the vehicle automation, the control of steering and velocity on vehicle systems is very important part in container transporter. In common sense, vehicle systems have lots of nonlinear parameters so we have many difficulties in designing the optimal controller of them. In this paper, we present a design of the TDOF PID controller using a hybrid schematic algorithm to control the steering system optimally. We used the single-track model to pre-test the designed controller before appling to AGV. We also used the ES(evolutionary strategy) and SA(simulated annealing) algorithms to construct the hybrid tuning algorithm for parameters of controller. Finally, we had the computer simulation to verify that our designed controller has better performance than the other one.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.221-228
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• 2005

Data storage was thought to be inside of or next to server cases but advances in networking technology make the storage system to be located far away from the main computer. In Internet era with explosive data increases, balanced development of storage and transmission systems is required. SAN(Storage Area Network) and NAS(Network Attached Storage) reflect these requirements. It is important to know the capacity and limit of the complex storage network system to got the optimal performance from it. The capacity data is used for performance tuning and making purchasing decision of storage. This paper suggests an analytic model of storage network system as queuing network and proves the model though simulation model.