• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1166-1176
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• 2017

Estimation errors of the rotor speed and position in sensorless control systems of Permanent Magnet Synchronous Motors (PMSM) will lead to low efficiency and dynamic-performance degradation. In this paper, a parallel-type extended nonlinear observer incorporating the nominal parameters is constructed in the stator-fixed reference frame, with rotor position, speed, and the load torque simultaneously estimated. The stability of the extended nonlinear observer is analyzed using the indirect Lyapunov's method, and observer gains are selected according to the transfer functions of the speed and position estimators. Taking into account the parameter inaccuracies issue, explicit estimation error equations are derived based on the error dynamics of the closed-loop sensorless control system. An equivalent flux error is defined to represent the back Electromotive Force (EMF) error caused by the inaccurate motor parameters, and a compensation strategy is designed to suppress the estimation errors. The effectiveness of the proposed method has been validated through simulation and experimental results.

• 전기학회논문지
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• 제60권5호
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• pp.1011-1016
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• 2011

This paper presents a robust current controller for a surface-mounted permanent magnet synchronous motor(SPMSM) by using a PI observer. The decoupling PI(proportional-integral) controller combined with an additional feed-forward compensation has been used for the current controller. The classical feed-forward compensation using velocity information and system parameters is not expected to achieve a robust performance against parameter uncertainties. This paper has adopted a PI observer for the feed-forward compensation to cope with parameter uncertainties without using velocity information. A simple PI observer has been designed to compensate the disturbances that represent velocity coupled terms and parameter uncertainties. Experimental results as well as computer simulations with 630W SPMSM confirm that the proposed approach can deal with the effects of the disturbance and improve the control performance.

• Journal of Power Electronics
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• 제16권6호
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• pp.2150-2161
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• 2016

Mechanical and electrical parameter uncertainties cause dynamic and static estimation errors of the rotor speed and position, resulting in performance deterioration of sensorless control systems. This paper applies an extended nonlinear observer to interior permanent magnet synchronous motors (IPMSM) for the simultaneous estimation of the rotor speed and position. Two compensation methods are proposed to improve the observer performance against parameter uncertainties: an on-line rotational inertia adjustment approach that employs the gradient descent algorithm to suppress dynamic estimation errors, and an equivalent flux error compensation approach to eliminate static estimation errors caused by inaccurate electrical parameters. The effectiveness of the proposed control strategy is demonstrated by experimental tests.

• 한국정밀공학회지
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• 제16권6호
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• pp.166-175
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• 1999

This paper describes a design and performance evaluation of robust controller which overrides unstable motion and pulls out quickly after water entry of underwater vehicle dropped from aircraft or surface ship. We use 6-DOF equation for model of motions and assume parameter uncertainty to reflect the difference of real motion from modelled motion equation. we represent a nonlinear system with uncertainty as Takagi and Sugeno's(T-S) fuzzy models and design controller stabilizing them. The fuzzy controller utilizes the concept of so-called parallel distributed compensation (PDC). Finally, we confirm stability and performance of the controller through computer simulation and hardware in the loop simulation (HILS).

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 A
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• pp.112-114
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• 1997

Recently sensorless PMSM is much studied for the industrial applications and home appliances. Most of sensorless algorithm are based on the motor equations of which coefficients are motor parameters. However, uncertainty of motor parameter effects the accuracy of speed estimation of PMSM. This paper investigates the robust speed control of sensorless PMSM which has robustness to parameter uncertainty or variation. The parameter compensation is performed through PI control of the speed error between the estimated speed and the real speed obtained from the measured current. The proposed algorithm is verified through the experiment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.32-35
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• 1987

An adaptive control scheme has been recognized as an effective approach for a robot manipulator to track a desired trajectory in spite of the presence of nonlinearties and parameter uncertainties in robot dynamic models. In this paper, an adaptive control scheme for a robot manipulator is proposed to design the self-tuning controller which combines the pole placement with the extended linearized perturbation model. And this control scheme has two components: a feadforward control and a feedback compensation control. Based on this, the controller is demonstrated by the simulation about position control of a three-link manipulator with payload and parameter uncertainty.

• 전자공학회논문지S
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• 제35S권6호
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• pp.46-54
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• 1998

본 논문은 파라미터 불확실성을 갖는 비선형 시스템을 안정화하며, 폐루프 시스템의 외란감쇠에 대한 $L_{2}$ 이득 제한조건을 만족시키는 견실 퍼지 $H^{\infty}$ 제어기 설계기법을 제시한다. 불확실성을 갖는 비선형 시스템을 불확실성을 갖는 Takagi-Sugeno(T-S) 모델로 표현하고 병렬 분산 보상(PDC : parallel distributed compensation)의 개념을 이용하여 제어기를 설계한다. 파라미터 불확실성을 갖는 T-S 퍼지모델에 대한 감쇠율을 만족하는 폐루프 시스템의 안정성 조건과 Lyapunov 함수를 이용하여 외란감쇠 조건을 유도하고, 선형 행렬 부등식(LMI: linear matrix inequality)을 이용하여 견실 퍼지 $H^{\infty}$ 제어기가 존재할 충분조건을 구한다. 마지막으로 불확실성을 갖는 비선형 시스템에 대한 퍼지 $H^{\infty}$ 제어기 설계 예를 보인다.

• 제어로봇시스템학회논문지
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• 제14권10호
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• pp.991-997
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• 2008

A new RMRAC scheme far the PMSM current regulation is proposed in a synchronous frame, which is completely free from the parameter's uncertainty. A current regulator of PMSM is the inner most loop of electromechanical driving systems and plays a foundation role in the control hierarchy. When the PMSM runs in high speed, the cross-coupling terms must be compensated precisely for large system BW. In the proposed RMRAC, the input signal is composed of a calculated voltage defined by MRAC law and an output of the disturbance compensator. The gains of feed forward and feedback controller are estimated by the proposed modified gradient method, where the system disturbances are assumed as filtered current regulation errors. After the compensation of the system disturbance from error information, the corresponding voltage is fed forward to control input to compensate for real disturbances. The proposed method robustly compensates the system disturbance and cross-coupling terms. It also shows a good realtime performance due to the simplicity of control structure. Through real experiments, the efficiency of the proposed method is verified.

• 전기학회논문지
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• 제58권1호
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• pp.173-180
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• 2009

It is difficult to predict non-stationary or chaotic time series which includes the drift and/or the non-linearity as well as uncertainty. To solve it, we propose an effective prediction method which adopts data preprocessing and multiple model TS fuzzy predictors combined with model selection mechanism. In data preprocessing procedure, the candidates of the optimal difference interval are determined based on the correlation analysis, and corresponding difference data sets are generated in order to use them as predictor input instead of the original ones because the difference data can stabilize the statistical characteristics of those time series and better reveals their implicit properties. Then, TS fuzzy predictors are constructed for multiple model bank, where k-means clustering algorithm is used for fuzzy partition of input space, and the least squares method is applied to parameter identification of fuzzy rules. Among the predictors in the model bank, the one which best minimizes the performance index is selected, and it is used for prediction thereafter. Finally, the error compensation procedure based on correlation analysis is added to improve the prediction accuracy. Some computer simulations are performed to verify the effectiveness of the proposed method.

• 전기학회논문지P
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• 제59권2호
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• pp.163-172
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• 2010

A robust positioning control system has been studied using a friction parameter observer and a recurrent fuzzy neural network based on the sliding model. To estimate a nonlinear friction parameters of the LuGre friction model, a dual friction model-based observer is introduced. In addition, an approximating method for a system uncertainty has been developed using a recurrent fuzzy neural network technique to improve positioning performance. Experimental results have been presented to validate the performance of a proposed intelligent compensation scheme.