• Steel and Composite Structures
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• v.8 no.2
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• pp.129-144
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• 2008

This paper demonstrates an application of the perturbation based stochastic finite element method (SFEM) for predicting the performance of structural systems made of composite sections with random material properties. The composite member consists of materials in contact each of which can surround a finite number of inclusions. The perturbation based stochastic finite element analysis can provide probabilistic behavior of a structure, only the first two moments of random variables need to be known, and should therefore be suitable as an alternative to Monte Carlo simulation (MCS) for realizing structural analysis. A summary of stiffness matrix formulation of composite systems and perturbation based stochastic finite element dynamic analysis formulation of structural systems made of composite sections is given. Two numerical examples are presented to illustrate the method. During stochastic analysis, displacements and sectional forces of composite systems are obtained from perturbation and Monte Carlo methods by changing elastic modulus as random variable. The results imply that perturbation based SFEM method gives close results to MCS method and it can be used instead of MCS method, especially, if computational cost is taken into consideration.

• Smart Structures and Systems
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• v.15 no.3
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• pp.897-911
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• 2015

This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.295-301
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• 2012

This paper deals with the design of robust DSMC (Discrete-Time Sliding Mode Control) scheme in order to overcome system uncertainty in steering system with mechanically joined structure. The proposed control scheme is one of robust control schemes based on system dynamics. Therefore, system dynamics required is not obtained from physical law but SCM (Signal Compression Method) through experiment in order to avoid complicate mathematical development and save time. However, SCM has a shortcoming that is the limitation of with $2^{nd}$ order linear model which does not include the dynamic of high-frequency band. Thus, considering system uncertainty, DSMC is designed. In addition, to reduce the chattering problem of DSMC, DSMC is derived from the reaching law and the Lyapunov stability condition. It is found that the proposed control scheme has robustness in spite of the perturbation of system uncertainty through computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.25-32
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• 1999

교류전동기 구동을 위한 산업용 전력전자 시스템은 전력회생용 양방향 컨버터, VVVF 인버터, 교류전동기 벡터제어기, 및 다양한 전기ㆍ기계적 연계 장치들을 포함하는 전기기계 복합시스템 특성을 지니기 때문에 전체 시스템에 대한 컴퓨터 시뮬레이션이 용이하지 않다. 일반적으로 이러한 복잡성을 해결하기 위한 방안으로서 시스템을 근사화시키고 이에 대한 수학적인 등가모델을 유도한 후 이를 이용하여 시뮬레이션을 행하고 있지만, 이 경우 실계통의 다이나믹특성을 정확히 표현할 수 없기 때문에 시뮬레이션 신뢰성이 저하될 수 있다 본 논문에서는 가변구조 제어기법에 의해 역률1 제어기능을 갖는 PWM 컨버터, VVVF 인버터 및 유도기 간접벡터제어기 둥을 포함하는 유도전동기 구동전력전자 시스템을 다이나믹 노드 기법(Dynamic Node Technique DNT)과 시뮬링크(Simulink)를 이용하여 실제회로 구성상태와 유사한 형태로 시뮬링크 윈도우상에서 설계하고, 이를 통해 시뮬레이션을 행할 수 있는 기법을 제시한다. 시뮬레이션 결과를 통하여 전력전자 시스템의 특성과 제시된 다이나믹 노드 기법과 시뮬링크를 이용한 시뮬레이션 기법의 유용성을 보였다.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.95-104
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• 1999

In this paper we propose a fast and precise control algorithm for a mobile robot, which aims at the self-tuning control applying two multi-layered neural networks to the structure of computed torque method. Through this algorithm, the nonlinear terms of external disturbance caused by variable task environments and dynamic model errors are estimated and compensated in real time by a long term neural network which has long learning period to extract the non-linearity globally. A short term neural network which has short teaming period is also used for determining optimal gains of PID compensator in order to come over the high frequency disturbance which is not known a priori, as well as to maintain the stability. To justify the global effectiveness of this algorithm where each of the long term and short term neural networks has its own functions, simulations are peformed. This algorithm can also be utilized to come over the serious shortcoming of neural networks, i.e., inefficiency in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.197-203
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• 1997

In this paper, we present a GP-PID(Generalized Predictive PID) controller which has the same structure as a generalized predictive control with steady-state weighting. The proposed controller can perform better than the conventional PID controller because it includes intrinsic delay-time compensator. The PID tuning parameters and delay-time compensator are calculated by equating the two degree of freedom PID to a linear form of GPC. The proposed controller is combined with a supervisor for safe start and self-tuning. GP-PID controller has been tested for various numerical models and an experimental stirred tank heater. As a result, it was observed that the proposed controller shows a satisfactory performance for variable delay as well as stochastic disturbance.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.270-273
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• 1996

A scheme of observer-based MFAC(Model Following Acceleration Control) system is proposed for the robustness control of DC servo position control systems. The proposed system is composed of LMFC, variable structure feedback controller, and reduced-order state observer. As the servo motor is controlled by the acceleration command, the total servo system becomes the acceleration control system. Simulation results show that the proposed system have robust properties against parameter variations and external disturbances.

• Proceedings of the KIPE Conference
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• 1996.06a
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• pp.13-16
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• 1996

A new instantaneous torque control technique is presented for a high performance control of a permanent magnet synchronous motor. Using the model reference adaptive system technique, the linkage flux of the motor is estimated and the torque is instantaneously controlled by the proposed torque controller combining with a variable structure control and space vector PWM. The proposed torque control provides the advantage of reducing the torque pulsation caused by the flux harmonics. This control strategy is applied to the high torque PM synchronous motor drives for direct drive systems and is implemented by using a software of the DSP TMS320C30. The experiments are carried out for this system and the results well demonstrate the effectiveness of the proposed control.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.363-366
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• 2000

본 논문에서는 브러쉬없는 직류전동기의 위치제어를 위한 직접적응 퍼지가변구조제어기를 설계한다. 가변구조제어는 시스템의 파라메터 변화나 외란에 둔감한 특성을 갖는 반면 떨림현상의 문제점을 가지고 있다. 떨림현상의 진폭은 시스템의 불확실정보를 최악의 상태로 가정한 후 결정되므로, 기존의 가변구조제어에서는 그 크기가 너무 크다. 또한 이런 불확실한 요소들의 최대값은 찾아내기도 어렵다. 본 논문에서는 불확실한 요소의 최대값을 최적으로 추정하기 위하여 퍼지 추론 기법을 사용한다. 아울러 소속함수의 원소들을 직접적응 기법에 의하여 자동 조정할 수 있는 기법을 추가한다. 이를 통하여 우수한 제어 성능을 얻을 수 있음을 확인한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.489-492
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• 2000

브러쉬없는 직류전동기의 위치제어를 위한 퍼지가변구조제어기를 설계한다. 특히 본 논문에서는 기존의 퍼지제어 기법에서 얻을수 있는 특징으로부터 하나의 전건부 변수만을 가지는 간단한 퍼지논리제어기의 설계를 기술한다. 가변구조제어는 시스템의 파라메터 변화나 외란에 둔감한 특성을 갖는다. 하지만 리칭페이스에서는 문제가 된다. 이를 개선하기 위하여 본 논문에서는 지수항을 추가한 비선형 슬아이딩면을 구성한다. 그리고 나서 비선형적 슬라이딩면과 슬라이딩면의 변화율을 입력으로하는 퍼지 제어기를 설계한다. 이러한 2-입력 퍼지가변구조제어기의 제어 규칙표로부터 슬라이딩면 하나만을 입력으로 가지는 단일입력 퍼지 가변구조 제어기를 설계한다. 이들 제어기의 성능을 입증하기 위하여 시뮬레이션과 실험을 수행한다.