• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.2
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• pp.131-138
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• 2007

In this paper, a novel nonlinear control method of the CVCF(constant voltage and constant frequency) output voltage for the three-phase PWM inverter with LC output filters is proposed. A nonlinear modeling including the output LC filters is linearized by feedback linearization theory, the controllers of which can be designed based on a linear control theory. It is applied to the DC/AC power conversion of the PWM inverter for stand-alone wind power generation system. It has been verified by the experimental results that the proposed control scheme gives high dynamic responses at load variation as well as a zero steady-state error.

• Journal of Power Electronics
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• v.11 no.3
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• pp.369-374
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• 2011

Usually, a LPF (low pass filter) is used in the feedback loop of a SRF (synchronous reference frame) - PLL (phase locked loop) system because the measured grid voltage contains harmonic distortions and sensor noises. In this paper, it is shown that the cut-off frequency of the LPF should be designed to suppress the harmonic ripples contained in the measured voltage. Also, a new design method for the loop gain of the PI-type controller in the SRF-PLL is proposed with consideration of the dynamics of the LPF. As a result, a better transient response can be obtained with the proposed design method. The LPF frequency and the PI controller gain are designed in coordination according to the steady state and dynamic performance requirements. Furthermore, in the proposed method, the controller gain and the LPF cut-off frequency are changed from their normal value to a transient value when a voltage disturbance is detected. This paper shows the feasibility and usefulness of the proposed methods through the computer simulations and experimental results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.2
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• pp.307-316
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• 1994

The rainfall forecasting model of the short term is improved at the point where meterological data is not gaged. In this study, the adopted model is based on the assumptions for simulation model of rainfall process, meteorological homogeneousness, prediction and estimation of meteorological data. A Kalman Filter technique is used for rainfall forecasting. In the existing models, the equation of the model is non-linear type with regard to rainfall rate, because hydrometer size distribution (HSD) depends on rainfall intensity. The equation is linearized about rainfall rate as HSD is formulated by the function of the water storage in the cloud. And meteorological input variables are predicted by emprical model. It is applied to the storm events over Taech'ong Dam area. The results show that root mean square error between the forecasted and the observed rainfall intensity is varing from 0.3 to 1.01 mm/hr. It is suggested that the assumptions of this study be reasonable and our model is useful for the short term rainfall forecasting at the ungaged point of the meteorological data.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.1
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• pp.1-8
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• 2004

The INS(Inertial Navigation System) provides high rate position, velocity and attitude data with good short-term stability while the GPS(Global Position System) provides position and velocity data with long-term stability. By integrating the INS with GPS, a navigation system can be achieved to Provide highly accurate navigation Performance. For the best performance, time synchronization of GPS and INS data is very important in GPS/INS integrated system But, it is impossible to synchronize them exactly due to the communication and computation time-delay. In this paper, to reduce the error caused by the measurement time-delay in GPS/INS integrated systems, error compensation methods using separate bias Kalman filter are suggested for both the loosely-coupled and the tightly-coupled GPS/INS integration systems. Linearized error models for the position and velocity matching GPS/INS integrated systems are Int derived by linearizing with respect to its time-delay and augmenting the delay-state into the conventional state equations for each case. And then separate bias Kalman Inter is introduced to estimate the time-delay during only initial navigation stage. The simulation results show that the present method is effective enough resulting in considerably less position error.

• Journal of Broadcast Engineering
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• v.1 no.2
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• pp.176-187
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• 1996

This paper deals with the accurate estimation of 3- D pose (position and orientation) of a moving object with reference to the world frame (or robot base frame), based on a sequence of stereo images taken by cameras mounted on the end - effector of a robot manipulator. This work is an extension of the previous work[1]. Emphasis is given to the 3-D pose estimation relative to the world (or robot base) frame under the presence of not only the measurement noise in 2 - D images[ 1] but also the camera position errors due to the random noise involved in joint angles of a robot manipulator. To this end, a new set of discrete linear Kalman filter equations is derived, based on the following: 1) the orientation error of the object frame due to measurement noise in 2 - D images is modeled with reference to the camera frame by analyzing the noise propagation through 3- D reconstruction; 2) an extended Jacobian matrix is formulated by combining the result of 1) and the orientation error of the end-effector frame due to joint angle errors through robot differential kinematics; and 3) the rotational motion of an object, which is nonlinear in nature, is linearized based on quaternions. Motion parameters are computed from the estimated quaternions based on the iterated least-squares method. Simulation results show the significant reduction of estimation errors and also demonstrate an accurate convergence of the actual motion parameters to the true values.