• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.840-843
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• 2003

본 논문은 임의의 입력지연을 갖는 Takagi-Sugeno (T-S) 퍼지 시스템의 관측기 기반 출력궤환 제어 시스템을 논의한다. 설계된 연속시간 T-S 퍼지 관측기 시스템을 영차의 샘플/홀드 함수를 이용하여 이산시간 관측기를 설계한다. 이때 플랜트와 관측기의 출력에러가 제어기를 통하여 궤환되기 때문에 이산화 과정에서 발생한 에러를 보정할 수 있다. 여기에서 시스템의 제어 입력은 임의로 변화하는 유한개의 상태를 갖는 마코프 확률과정으로 표현한다. 생성된 시스템의 확률적 안정 가능성 조건은 선형 행렬 부등식의 형태로 표현한다. 이러한 결과를 2자유도 헬리콥터의 모델에 대한 모의실험을 통하여 효용성을 확인한다.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.107-114
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• 2013

In this paper, we propose controller to control the acceleration of unmanned aircraft turbojet engine. The high-gain observer to estimate the rotational speed of compressor is used, and the turbojet engine controller applying fuzzy heuristic techniques and PID control algorithm are designed. fuzzy PID controller produces the flow control input to prevent the surge and flame-out phenomena at the acceleration and deceleration of the turbojet engine. The standard acceleration is set and the fuel flow control is defined by the fuzzy heuristic. Computer simulations are performed using MATLAB in order to verify the performance of the proposed controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.2
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• pp.157-164
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• 2007

In this paper, a novel sensorless drive for brushless DC (BLDC) motor using the fuzzy back-EMF observer is proposed to improve the performance of conventional sensorless drive methods. Existing sensorless drive methods of the BLDC motor have low performance at transients or low speed range and occasionally require additional circuits. To cope with these problems, the back-EMF of the BLDC motor must be precisely estimated by a fuzzy logic, which is suitable to estimate the back-EMF which has a trapezoidal shape. The proposed algorithm using fuzzy back-EMF observer can achieve robust control for the change of an external condition and continuously estimate position of the rotor at transients as well as at steady state. The superiority of the proposed algorithm is proved through the simulation compared with other sensorless drive methods.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1439-1450
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• 2013

This paper investigates a robust neuro-fuzzy control (NFC) method which can accurately follow the speed reference of an interior permanent magnet synchronous motor (IPMSM) in the existence of nonlinearities and system uncertainties. A neuro-fuzzy control term is proposed to estimate these nonlinear and uncertain factors, therefore, this difficulty is completely solved. To make the global stability analysis simple and systematic, the time derivative of the quadratic Lyapunov function is selected as the cost function to be minimized. Moreover, the design procedure of the online self-tuning algorithm is comparatively simplified to reduce a computational burden of the NFC. Next, a rotor angular acceleration is obtained through the disturbance observer. The proposed observer-based NFC strategy can achieve better control performance (i.e., less steady-state error, less sensitivity) than the feedback linearization control method even when there exist some uncertainties in the electrical and mechanical parameters. Finally, the validity of the proposed neuro-fuzzy speed controller is confirmed through simulation and experimental studies on a prototype IPMSM drive system with a TMS320F28335 DSP.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1187-1193
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• 2011

In this paper, proposed controller preventing compressor surge and reducing the acceleration time of the fuel flow control system for turbo-jet engine. Turbo-jet engine controller is designed by applying fuzzy PID control algorithm and high-gain observer. Observer is used to estimate to compressor rotation speed of turbo-jet engine. Result of fuzzy inference is used as the fuel flow control inputs for preventing compressor surge and flame-out in turbo-jet engine. The controller is designed to converge to the desired speed quickly and safely. Using MATLAB to perform computer simulations verified the performance of the proposed controller.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.127-134
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• 2008

In this paper, we propose a robust adaptive backstepping control of induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time-varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the fuzzy neural network(FNN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.127-128
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• 2008

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.4
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• pp.343-351
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• 2000

This paper introduces a new rotor position estimation algorithm for the Switched Reluctance Motor, based on the magnetizing curves only at aligned and unaligned rotor positions. The flux linkage is calculated by measured data from phase voltage and phase current, and calculated data are used as the input of magnetizing profiles for rotor position detection. The fuzzy flux observer using novel knowledge-based fuzzy controller are presented to achieve sensorless control of the SRM. The method for selecting optimal angle is proposed for the rotor position detection. The robustness of the proposed algorithm is proved through the comparison of the simulation and experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.506-506
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• 2000

To improve control performance of a non-linear system, many other researches have used the sliding mode control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However. this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network generates the control input for compensating unmodeled dynamics terms and disturbance. And, the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors to converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluating control performance of the proposed approach. tracking control simulation is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.700-705
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• 2012

This paper addresses an intelligent digital redesign (IDR) technique for observer-based output-feedback control systems, in order to efficiently convert a pre-designed Takagi-Sugeno fuzzy model-based analog controller into a sampled-data one in the sense of state matching. A delta operator is used to get an asymptotic relation between the analog and the sampled-data control systems. The IDR problem is viewed as a minimization problem of the norm distances between linear operator to be matched. The condition is represented as linear matrix inequalities, and the separation principle on the IDR is shown.