• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.1
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• pp.1-12
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• 1999

A design and DSP-based implementation of robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) under the unknown parameter variations and speed measurement error is presented. The model reference adaptive system(MRAS) based adaptation mechanisms for the estimation of slowly varying parameters are derived using the MIT rule. For the disturbances or quickly varying parameters, a quasilinearized and decoupled model which includes the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is designed and compared with the conventional controller which employs Proportional plus Derivative(PD) control. To show the validity of the proposed scheme, simulations and DSP-based experimental works are carried out and compared with the conventional control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.120-124
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• 1987

Linear time invariant systems are considered. It is assumed that only partial state variables are observable for feedback control. In this study, a new method is presented for designing a stat e feedback controller. It is based on augmenting the original system by additional integrator and using time delayed feedback of observable variables. Several examples and its computer simulation results are given to show the effectiveness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.3
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• pp.31-42
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• 1985

Thig paper used two feedback sensors, that is, potentiometer and tachometer in order to control DC motor. Also, the state feedback and kalman regular type in the linear system or the state feedback and on-off relay type in the non-linear system are used as control meth-ods for optimal control values. This compared and analyzed the control estimate of tracking angles by the estimate of three branches of methods of position and speed measured, position and speed by PD and position, speed and covariance by an observer.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.424-429
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• 2019

The evolution of networking technology such as commercialization of 5G systems provides foundation for information exchange and control of systems over the network. In addition, importance of controlling a system with delay is increasing significantly, since various phenomena in the network are associated with delay. In this paper, with a predictive control which has been studied for designing a controller with low complexity, we propose a novel predictive control for a system with multi-inputs such that it can keeps the complexity almost the same regardless of the number of inputs and degree of delay. The asymptotic stability of the proposed control with a static output feedback is also proved. The numerical simulation shows that the proposed method is superior in complexity and the performance of finding feasible controllers to the existing predictive control and a conventional method based on augmented states.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.214-221
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• 1998

A new control approach using neural network for the robust position control of a BRUSHLESS direct drive(BLDD) motor is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust BLDD motor system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system will be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained by error back-propagation at each sample period to accommodate the possible variations in the parameters or load torque. And the state space analysis is performed to obtain the state feedback gains systematically. In addition, the robustness is also obtained without affecting overall system response.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.1
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• pp.112-115
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• 2003

Robust control for servo control system in needed according to the highest precision of industrial automation. However, when a servo control system has an effect of disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem in this paper, Hybrid control method of Main controller(PIU)-Differential Supervisory controller is presented. Main controller is operated as a feedback controller. Differential Supervisory controller as a assistant controller is operated when state in unstable disturbance. The robust control function of Differential Supervisory controller is demonstrated by Speed control of Motor.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.5
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• pp.8-17
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• 2002

This paper considers the problems of robust decentralized control for uncertain discrete-time large-scale systems with delays in interconnections and state feedback gain perturbations. Based on the Lyapunov method, the state feedback control design for robust stability is given in terms of solutions to a linear matrix inequality (LMI), and the measure of non-fragility in controller is presented. The solutions of the LMI can be easily obtained using efficient convex optimization techniques. A numerical example is included to illustrate the design procedures.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.520-525
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• 2003

This paper concerns a design methodology of observer-based output-feedback digital controller for Takagi-Sugeno(TS) fuzzy systems using intelligent digital redesign (IDR). The term of IDR involves converting an analog fuzzy-mode-based controller into an equivalent digital one in the sense of state-matching. The considered IDR problem is viewed as convex minimization problems of the norm distances between linear operators to be matched. The stability condition is easily embedded and the separations principle is explicitly shown.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.92-97
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• 2005

This paper discusses an intelligent digital redesign technique for designing a fuzzy pulse-width-modulated (PWM) control. First when we are given a well-designed fuzzy analog control, the equivalent digital control is intelligently redesigned. Using the similar technique we intelligently redesign the fuzzy PWM control from the intelligently redesigned fuzzy digital control. A stabilizability of the intelligently redesigned PWM control is rigorously analyzed.