• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.129-136
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• 2002

This paper presents a $H_{\infty}$ robust controller with parameter estimation in polynomial approach. For good performance of a uncertain system, the parameters are estimated by RLS algorithm. The controller minimizes the sum of $H_{\infty}$ norm between sensitivity function and complementary sensitivity function by employing the Youla parameterization and polynomial approach at the same time. A numerical example and its simulation results are given to show the validity of the proposed controller.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.426-429
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• 1989

The robust self-tuning controller is designed which is guaranteed the asymptotic regulation and tracking in the presence of a bounded parameter perturbation. The global stability in the presence of a finite noise and disturbance is ensured. The controller has a error driven structure, and involves the common model of a disturbance and reference input in the internal model. The adaptive system tunes the controller parameters such that the quadratic performance index which involves a weighting factor is optimized.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.70-72
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• 2009

In this paper, nonlinear active noise control(ANC) of a 3rd-order Volterra system, which is robust to background noise variation, is proposed along with a variable step-size Gauss-Seidel pseudo affine projection(VSSGS-PAP) algorithm. Simulation results demonstrate that the proposed approach yields better nonlinear ANC performance in a background noise variation environment, compared with the conventional methods for the nonlinear ANC.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.3
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• pp.62-68
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• 2006

In this paper, an adaptive input-output linearization and zero dynamics control of three phase AC/DC converter are proposed. For achieving output do voltage regulation with unity power factor, the q-axis current of the rotating d-q frame is regulated to zero and the output do voltage is controlled to track a given reference voltage $V_r$. The proposed scheme is robust to the parametric uncertainty md load current of the converter due to the adaptation process. The simulation results are presented to illustrate the performance and feasibility of the proposed control scheme.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1172-1175
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• 2001

Recently, vector control without a speed sensor for an inverter induction motor system has been developed. In this paper describes the vector control system estimates rotor speed based on FMRAS(Flux Model Reference Adaptive System). Because of improving the initial condition and drift problem by pure integrator is eliminated, we can be expected to rapid responsibility of the speed estimation. The stability of speed estimator is proved on the basis of hyperstability theory. Proposed control system used TMS320C31 DSP for high speed processing. The effectiveness of the proposed system is verified by simulation and experimental results. This result shows that the highly characteristic speed estimation and robust character of load regulation.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1860-1861
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• 2006

In this paper, we design a robust controller of biped robot system with uncertainties, using recurrent neural network. In our proposed control system, we use the self-recurrent wavelet neural network (SRWNN). The SRWNN makes up for the weak points in wavelet neural network(WNN). While the WNN has fast convergence ability, it dose not have a memory. So the WNN cannot confront unexpected change of the system. However, the SRWNN, having advantage of WNN such as fast convergence, can easily encounter the unexpected change of the system. For stable walking control of biped robot, we use sliding mode control (SMC). Here, uncertainties are predicted by SRWNN. The weights of SRWNN are trained by adaptive laws based on Lyapunov stability theorem. Finally, we carry out computer simulations with a biped robot model to verify the effectiveness of the proposed control system,.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.540-543
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• 1999

This paper describes a speed sensorless algorithm for vector control system with compensated stator resistance and rotor time constant of induction motor using a model reference adaptive system(MRAS). The system are composed of two MRAC, one is a rotor speed estimation and a stator resistor identification by back-EMF observer, other is used to identify rotor time constant by magnetizing current observer, so that the estimation can be cover a very low speed range with a robust control. The suggest control strategy and estimation method have been validated by simulation study. In the simulation using Matlab/Simulik, the proposed speed sensorless vector control system are shown to operate very well in spite of variable rotor time constant and load fluctuation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.132.4-132
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• 2001

Field robot represented by excavator can be applied for various kinds of working in manufacturing, construction, agriculture etc. because of the flexibility of its multi-joint mechanism and the high power of hydraulic actuators. In general, the dynamics of field robot have strong coupling, various kinds of non-linearity, and time varying parameters according to working conditions. Therefore, it is very difficult to describe the system well, and design controller systematically based on its model. This paper established the mathematical model of field robot driven by electro-hydraulic servomechanism and constructed the adaptive control system robust to external load variations. The proposed control system for the field robot was evaluated by the computer simulation, and the performance results of trajectory tracking were compared with that of PID control system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.151-151
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• 2000

The objective of this paper is to develop the new robust and adaptive control system against external environments as applying the probabilistic recognition which is one of the inherent properties of immune system, ability of learning and memorization, and regulation theory of immune network to the system under engineering point of view. In this paper, HIA(Humoral Immune Algorithm) PID controller using Neural Network Identifier was proposed to drive the autonomous guided vehicle(AGV) more effectively. To verify the performance of the proposed HIA PID controller, some experiments for the control of steering and speed of that AGV are performed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.420-424
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• 2006

본 논문에서는 외란을 갖는 불확실한 비선형 시스템을 제어하기 위하여 $H^{\infty}$ 제어를 이용한 강인 간접 적응 퍼지 관측기를 설계하여 상태변수를 관측하고 외란관측기를 설계하여 시스템의 외란을 제거하는 강인한 제어기를 구성한다. 제안된 외란관측기는 시스템과 외란의 대역폭보다 큰 궤환 이득을 가짐으로써 기존의 역플랜트 모델 또는 퍼지 기반의 외란관측기 보다 간단한 구조를 가지고 외란과 시스템 모델링 오차의 합을 관측해 낼 수 있다. 본 논문에서는 도립진자 시스템의 모의실험을 통하여 관측기, 외란관측기와 제어기의 성능을 평가한다.