• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.523-530
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• 2007

Crane systems are very important in industrial fields to carry heavy objects such that many investigations about control of the systems are actively conducted for enhancing its control performance. This paper presents an adaptive control approach using the model matching for a complex 3-DOF nonlinear crane system. First, the system model is linearized through feedback linearization method and then PD control is applied in the approximated model. This linear model is considered as nominal to derive corrective control law for a perturbed crane model using Lyapunov theory. This corrective control is primitively aimed to compensate real-time control deviation due to partially known perturbation. We additionally study stability analysis of the crane control system using Lyapunov perturbation theory. Evaluation of our control approach is numerically carried out through computer simulation and its superiority is demonstrated comparing with the classical control.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.4
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• pp.33-42
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• 2010

The induction motor drive applied to field oriented control is widely used in industry applications. However, it is deceased performance and authenticity by saturation, temperature changing, disturbance and parameters changing because modeling of induction motor is nonlinear and complex. In order to control variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field oriented conditions. This paper proposes self tuning PI controller based on fuzzy-neural network(FNN)-PI controller that is implemented using fuzzy control, neural network, and adaptive fuzzy controller(AFC). Also, this paper proposes estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FNN-PI, AFC and ANN controller. Also, this paper proposes the anlysis results to verify the effectiveness of controller.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.4
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• pp.618-623
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• 2008

This paper presents a design method of the Interpolation-based adaptive LQ controller that is accomplished by getting the final controller interpolated with each gain of sub-LQ controllers. The Lagrange interpolation method is used in the scheme. The proposed controller is useful to control nonlinear systems which are especially changed the system parameters. The design method is illustrated by an application to the stabilization and tracking problems of an inverted pole system on a cart. Several cases of simulations are carried out in order to validate the control effectiveness and robustness. The simulation results are compared with those of LQ controller and prove the better control performance than LQ controller.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.2
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• pp.159-163
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• 2008

In this paper, a simplified type of adaptive controller using Nussbaum gain for the control of the spacecrapt with elastic appendages is suggested. This method doesn't need the information of the high frequency components in transfer function. While the pitch angle tracks the desired value by this method, the elastic modes are also stabilized. Only pitch angle and the pitch rate are used for the design of the output feedback controller. Especially all system parameters and the high frequency gain are assumed to be unknown. For design simplicity, a controller is designed by using only the linear part, and it's shown to satisfy the nonlinear system by the simulation with basic explanations. By using the Lyapunov function, the stability of the suggested algorithm is demonstrated, and also the effectiveness of the suggested algorithm is verified by showing the computer simulation results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.178-183
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• 1995

본 연구에서는 플랜트 잡음이 강한 음향 환경에서 기존의 인버스 필터링 방법에 적용 선형 증진기를 부착하여 부가경로 전달함수의 온라인 모델링과 주소음원에 대한 제어 시뮬레이션을 수행하여 다음과 같은 결과를 얻었다. 첫째로, 신호대 잡음비가 낮은 음향 환경에서 적응 선형 증진기를 이용하여 플랜트 잡음을 제거함으로써 부가경로 전달함수의 온라인 모델링을 수행할 수 있었다. 둘째로, 실제의 부가경로 전달함수가 변한 상태에서 제안된 알고리즘을 이용하여 제어 시뮬레이션을 수행하여 주소음원에 대한 제어와 정확하게 새로운 부가경로 전달함수를 예측할 수 있었다. 향후 본 연구에서 제안된 알고리즘을 실시간 어셈블리화하여 능동 소음 제어 실험한 결과를 발표할 예정이다.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.130-135
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• 2007

This paper deals with a controller design for a 2 dimensional aeroelatic model which has unknown parameters including polynomial type nonlinearity. Actually in case of state and acuator signal having magnitude, rate and bandwidth limitations, the controller can't be implemented and so in each case, a filter is used for implementation. First, error signals are defined upon the backstepping theory, and tracking error signals are also defined due to command signal and filter signals and then compensated tracking error signals are defined. Lastly, a Lyapunov function is defined for the stabilization and from this method, an adaptive law is derived. Simulations are done for the demonstrtion of the effectiveness of the algorithms.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.17-20
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• 2001

In this paper, we design a nonlinear adaptive controller using wavelet neural network. The method proposed in this paper performs for a nonlinear system with unknown parameters, identification with using a wavelet neural network, and then a nonlinear adaptive controller is designed with those identified informations. The advantage of the proposed control method is simple to design a controller for unknown nonlinear systems, because we use the identified informations and design parameters are positioned within a negative real part of s-plane. The simulation results showed the effectiveness of proposed controller design method.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.437-440
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• 1998

In this paper, the design method of fuzzy neural network(FNN) controller using indirect adaptive control technique is presented for controlling chaotic nonlinear systems. Firstly, the fuzzy model identified with a FNN in off-line process. Secondly, the trained fuzzy model tunes adaptively the control rules of the FNN controller in on-line process. In order to evaluate the proposed control method, Indirect adaptive control method is applied to the representative continuous-time chaotic nonlinear systems, that is, the Duffing system and the Lorenz system. Simulations are done to verify the effectivencess of controller.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.921-923
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• 1999

In adaptive fuzzy control, fuzzy systems are used to approximate the unknown plant nonlinearities. However, because of the approximating error introduced into the feedback loop, it is difficult to guarantee the stability of the adaptive control algorithm. This paper presents a robust control algorithm against the reconstruction error and uniform boundedness of the all signals is estabilished in the Lyapunov sense.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.108-114
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• 2009

This paper proposes the new hybrid adaptive controller for fast response time and precision control of automation system which exist deadzone or non-linearity of system. The proposed system, which provides the improvement in terms of the control region in high speed and precision control, first used the fuzzy control method for fast response time and when the error reaches the preset value, used the PLL method designing PFD improved jitter for precision control. The new designed PFD improves the jitter noise and response characteristic without generating deadzone. The theoretical and experimental studies have been carried out. The presented results from the above investigation show considerably improved performance in the position control of automation system.