• 대한전기학회논문지:시스템및제어부문D
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• 제50권1호
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• pp.22-30
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• 2001

This paper describes a neural network based fuzzy PID control scheme. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriated PID gains in nonlinear systems and systems with long time delay and so on. In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a neural network based self tuning fuzzy PID controller of which output gains were adjusted automatically. The tuning parameters of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods. Then they were adjusted by using proposed neural network learning algorithm. Proposed controller was simple in structure and computational burden was small so that on-line adaptation was easy to apply to. The experiment on the magnetic levitation system, which is known to be heavily nonlinear, showed the proposed controller's excellent performance.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.525-530
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• 2003

This paper focuses on design of nonlinear power plant controller using immune based multiobjective fuzzy approach. The thermal power plant is typically regulated by the fuel flow rate, the spray flow rate, and the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature. the change of the dynamic characteristics in the steam-turbine system. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. These parameters tuned by multiobjective based on immune network algorithms could be used for the tuning of nonlinear power plant.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권8호
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• pp.353-362
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• 2006

This paper illustrates the practical design procedure on a position control of an electrical fin actuator for the guided missile using Time Delay Control(TDC) and Enhanced Time Delay Observer(ETDO). Since TDC is robust to the model uncertainties such as the parameter variation and the external disturbance, it has been frequently used in nonlinear control systems. For a position control of an electrical fin actuator in the missile system, TDC requires the velocity sensor as well as the position sensor. To resolve the problems of the cost, the space and the malfunction due to the velocity sensor, ETDO is used as the velocity observer. ETDO is enhanced version of TDO that has the problems of the reconstruction errors and the restriction on selecting its gains. To maximize the control performance, the parameters of ETDO are optimized by using the genetic algorithm. The effectiveness of this approach is proved through a series of simulation studies and experiments, and the designed controller is compared with the typical TDC and TDC using the reduced oder observer.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.955-959
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• 2003

A technique for realizing linear phase IIR filters has been proposed by Powell-Chau which gives a real-time implementation of H(z-1).H(z), where H(z) is a causal nonlinear phase IIR filter. Powell-Chau system is linear but not timeinvariant system. Therefore, that system has group delay response that exhibits a minor sinusoidal variation superimposed on a constant value. In the signal processing, this oscillation seriously degrade the signal quality. Unfortunately, that system has a large sample delay of 4L and also more computational complexity. Proposed system is present a reduced computational complexity technique by moved the numerator polynomial of H(1/z) out to cascade with causal filter H(z) and remain only all-pole of H(1/z), then applied truncated infinite impulse response to finite with truncated IIR filtel $H_L$(z) and L sample delay to subtract the output sequence from the top and bottom filter. Proposed system is linear time invariance and group delay response and total harmonic distortion are also improved.

• Smart Structures and Systems
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• 제31권3호
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• pp.259-273
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• 2023

Real-time hybrid simulation (RTHS) is an effective experimental technique for structural dynamic assessment. However, time delay causes displacement de-synchronization at the interface between the numerical and physical substructures, negatively affecting the accuracy and stability of RTHS. To this end, the authors have proposed a model-based adaptive control strategy with a Kalman filter (MAC-KF). In the proposed method, the time delay is mainly mitigated by a parameterized feedforward controller, which is designed using the discrete inverse model of the control plant and adjusted using the KF based on the displacement command and measurement. A feedback controller is employed to improve the robustness of the controller. The objective of this study is to further validate the power of dealing with a nonlinear control plant and to investigate the potential challenges of the proposed method through actual experiments. In particular, the effect of the order of the feedforward controller on tracking performance was numerically investigated using a nonlinear control plant; a series of actual RTHS of a frame structure equipped with a magnetorheological damper was performed using the proposed method. The findings reveal significant improvement in tracking accuracy, demonstrating that the proposed method effectively suppresses the time delay in RTHS. In addition, the parameters of the control plant are timely updated, indicating that it is feasible to estimate the control plant parameter by KF. The order of the feedforward controller has a limited effect on the control performance of the MAC-KF method, and the feedback controller is beneficial to promote the accuracy of RTHS.

• Smart Structures and Systems
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• 제14권6호
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• pp.1173-1196
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• 2014

Real-time dynamic substructuring tests have been conducted on a cable-deck system. The cable is representative of a full scale cable for a cable-stayed bridge and it interacts with a deck, numerically modelled as a single-degree-of-freedom system. The purpose of exciting the inclined cable at the bottom is to identify its nonlinear dynamics and to mark the stability boundary of the semi-trivial solution. The latter physically corresponds to the point at which the cable starts to have an out-of-plane response when both input and previous response were in-plane. The numerical and the physical parts of the system interact through a transfer system, which is an actuator, and the input signal generated by the numerical model is assumed to interact instantaneously with the system. However, only an ideal system manifests a perfect correspondence between the desired signal and the applied signal. In fact, the transfer system introduces into the desired input signal a delay, which considerably affects the feedback force that, in turn, is processed to generate a new input. The effectiveness of the control algorithm is measured by using the synchronization technique, while the online adaptive forward prediction algorithm is used to compensate for the delay error, which is present in the performed tests. The response of the cable interacting with the deck has been experimentally observed, both in the presence of delay and when delay is compensated for, and it has been compared with the analytical model. The effects of the interface delay in real-time dynamic substructuring tests conducted on the cable-deck system are extensively discussed.

• Advances in concrete construction
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• 제9권4호
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• pp.407-412
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• 2020

Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of concrete frame structures that adopt active controllers. Fuzzy theory is a relatively appropriate method but susceptible to human subjective experience to decrease the performance. To guarantee the stability of multi-time delays complex system with multi-interconnections, a delay-dependent criterion of evolved design is proposed in this paper. Based on this criterion, the sector nonlinearity which converts the nonlinear model to multiple rule base of the linear model and a new sufficient condition to guarantee the asymptotic stability via Lyapunov function is implemented in terms of linear matrix inequalities (LMI). A numerical simulation for a three-layer reinforced concrete frame structure subjected to earthquakes is demonstrated that the proposed criterion is feasible for practical applications.

• 대한토목학회논문집
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• 제40권3호
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• pp.303-314
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• 2020

수자원분야에서 이용되는 강우에 따른 유역의 수문학적 시스템, 도시지역 및 하천에 대한 수리학적 시스템은 비선형성이 강하고 많은 변수들을 포함하고 있다. 이러한 특성을 가진 시계열 자료에서 기계학습을 통한 예측은 예측시점 이전의 자료 특성을 반영하지 못하는 등 기본적인 신경망으로는 부족한 상황이 발생하기도 한다. 본 연구에서 적용할 강우-유출량과 같이 비선형성이 강하고 시간종속성이 높은 복잡한 시계열 자료를 예측하기 위해 신경망의 학습능력을 극대화한 순환형 동적 신경망(Recurrent Dynamic Neural Network)의 한 종류인 동시에, 시간 지연 신경망(Time-Delay Neural Network)의 특성을 가진 비선형 자기회귀(NARX, Nonlinear Autoregressive Exogenous Model) 인공신경망을 사용하였다. 이를 태화강 지방하천 구간에 적용하여 NARX 인공신경망의 시간 지연 매개변수를 10분에서 120분까지 조정하며 모의한 결과에 대해 여러 통계지표를 이용해 정량적으로 평가하였다. 그 결과 지연시간이 증가할수록 효율계수(NSE)가 0.530에서 0.988으로 증가하고, 평균제곱근편차(RMSE)가 379.9 ㎥/s에서 16.1 ㎥/s로 감소하는 등 정교한 예측이 가능함을 확인하였다.

• 전자공학회논문지B
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• 제31B권10호
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• pp.44-52
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• 1994

In this paper, we assume that the dynamics of DC motor and nonlinear load are unknown. We propose an inverse dynamic model of DC motor and nonlinear load using the artificial neural network and construck speed control system based on the proposed dynamic model. We also propose another dynamic model with speed prediction scheme using the artificial neural network that removes the undesirable time delay effect caused by the computation time during the real-time control. We suggest a dynamic model which has arbitrary number of speed arguments and is especially effective when the motor and load has large moment of inertia. Next, we suggest a controller that combine the neurocontrol and PID control with constant gain. We show that the proposed neurocontrol systems have capabilities of noise rejection and generalization to have good velocity tracking through computer simulations and experiments.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.315-320
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• 2003

This paper presents a control augmentation system (CAS) based on the dynamic model inversion (DMI) architecture for a highly maneuverable aircraft. In the application of DMI not treating actuator dynamics, significant instabilities arise due to limitations on the aircraft inputs, such as actuator time delay based on dynamics and actuator displacement limit. Actuator input saturation usually occurs during high angles of attack maneuvering in low dynamic pressure conditions. The pseudo-control hedging (PCH) algorithm is applied to prevent or delay the instability of the CAS due to a slow actuator or occurrence of actuator saturation. The performance of the proposed CAS with PCH architecture is demonstrated through a nonlinear flight simulation.