• 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.

• Steel and Composite Structures
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• v.26 no.4
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• pp.453-461
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• 2018

In this paper, nonlinear vibrations of the unsymmetrical laminated composite beam (LCB) on a nonlinear elastic foundation are studied. The governing equation of the problem is derived by using Galerkin method. Two different end conditions are considered: the simple-simple and the clamped-clamped one. The Hamiltonian Approach (HA) method is adopted and applied for solving of the equation of motion. The advantage of the suggested method is that it does not need any linearization of the problem and the obtained approximate solution has a high accuracy. The method is used for frequency calculation. The frequency of the nonlinear system is compared with the frequency of the linear system. The influence of the parameters of the foundation nonlinearity on the frequency of vibration is considered. The differential equation of vibration is solved also numerically. The analytical and numerical results are compared and is concluded that the difference is negligible. In the paper the new method for error estimation of the analytical solution in comparison to the exact one is developed. The method is based on comparison of the calculation energy and the exact energy of the system. For certain numerical data the accuracy of the approximate frequency of vibration is determined by applying of the suggested method of error estimation. Finally, it has been indicated that the proposed Hamiltonian Approach gives enough accurate result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.9
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• pp.1376-1385
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• 1993

This paper presents a new dynamic model which is represented by the second order differenatial equation and itcludes the robot arm dynamics as well as the actuator dynamics. The model exhibits excellent performance in the steady state and transient response. In addition the time varing nonlinear and coupled dynamic system has been linearized and decoupled by using nonlinear feedback and linearization method. In this case a pole assignment law is used to improve stability, and the optimal control altorithm is applied to the error equation to minimize the path error. In applying the proposed algorithm to the three joint manipulator with actuators, we obtained very encouraging results.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.307-310
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• 2006

We consider the problem of constructing observers for nonlinear systems with unknown inputs. It is shown that under some conditions, there exists an observer estimating the states of nonlinear systems with unknown inputs. Nonlinear observer design method using observer error linearization and the design technique of unknown input observer(UIO) for linear systems are used to derive conditions. Some illustrative examples are included. In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller.The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.72-78
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• 2005

This paper describes the design of a robust output-feedback controller for a single-input single-output nonlinear dynamical system with a full relative degree. While all the previous research works on the output-feedback control are based on dynamic observers, a new state estimator which uses the past values of the measurable system output is proposed. We name it backward-difference state estimator since the derivatives of the output are estimated simply by backward difference of the present and past values of the output. The disturbance generated due to the error between the estimated and real state variables is compensated using an additional robustifying control law whose gain is tuned adaptively. Overall control system guarantees that the tracking error is asymptotically convergent and that all signals involved are uniformly bounded. Theoretical results are illustrated through a simulation example of inverted pendulum.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.1
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• pp.99-106
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• 2001

In this paper, an 1-Watt amplifier for IMT-2000 was designed and fabricated using feedfarward method which has the highest linearity and wide bandwidth. Since feedforward is sensitive to surroundings for example heat, input power level, time and so on, adaptive controller using micro controller is adopted. We fabricated a HPA with 35 dB gain, 40 dBm of 1-dB compression point, and utilized variable attenuator and variable phase shifter using reflection type to cancel loop signal. From the measured results, the fo11owing facts were obtained, in signal loop, main carrier over 35 dB was suppressed and error signal over 30 dB is cancelled in error loop, IMD characteristics above 60 dBc were obtained.

• Journal of Power Electronics
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• v.12 no.5
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• pp.778-786
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• 2012

In this paper, a novel scheme for the condition monitoring of lithium polymer batteries is proposed, based on the sigma-point Kalman filter (SPKF) theory. For this, a runtime-based battery model is derived, from which the state-of-charge (SOC) and the capacity of the battery are accurately predicted. By considering the variation of the serial ohmic resistance ($R_o$) in this model, the estimation performance is improved. Furthermore, with the SPKF, the effects of the sensing noise and disturbance can be compensated and the estimation error due to linearization of the nonlinear battery model is decreased. The effectiveness of the proposed method is verified by Matlab/Simulink simulation and experimental results. The results have shown that in the range of a SOC that is higher than 40%, the estimation error is about 1.2% in the simulation and 1.5% in the experiment. In addition, the convergence time in the SPKF algorithm can be as fast as 300 s.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.387-393
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• 2017

This paper focuses on a horizontal waypoint tracking and a speed control of large diameter unmanned underwater vehicles (LDUUVs) with X-stern configuration plane. The concerned design problem is converted into an asymptotic stabilization of the error dynamics with respect to the desired yaw angle and surge speed. It is proved that the error dynamics under the proposed control scheme based on the linear control and the feedback linearization can be considered as a cascade system; the cascade system is asymptotically stable if its nominal systems are so. This stability connection enables to separately deal with the waypoint tracking problem and the speed control one. By using the sector nonlinearity, the nominal system with nonlinearities is modeled as a polytopic linear parameter varying (LPV) system with parametric uncertainties. Then, sufficient linear matrix inequality (LMI) conditions for its asymptotic stabilizability are derived in the sense of Lyapunov stability criterion. An example is given to show the validity of the proposed methodology.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.478-484
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• 2002

Linear towed arrays (LTA) have a nonlinear shape due to tow vessel motion, ocean swells and currents. By reasons of nominally linear shape, various towed array shape estimation techniques have been developed since the perturbed shape cause the error in target detection. In this paper,, we propose the beamforming method for the perturbed LTA with simple structure. The proposed method linearizes a nonlinear phase of steering vector with position information measured by two reference sensors. It can be proved using some properties of Markov transition matrix, and iteration number of linearization process is decided by variance of cross phase difference. As a result of computer simulation in the ocean environment, beampattern of the proposed method is almost same with the ideal case in my type of array shape. In the signal-to-noise ratio (SNR) performance simlation, the DOA estimation performance of the proposed beamforming method is evaluated, and the comparison with Bartlett beamformer of the LTA shows that the proposed method can estimate. the spatial characteristic of sources more accuracy.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.683-688
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• 2017

The unscented Kalman filter features a direct transforming process involving unscented transformation for removing the linearization process error that may occur in the extended Kalman filter. This paper proposes a reduced-order unscented Kalman filter for the sensorless control of a permanent magnet synchronous motor. The proposed method can reduce the computational load without degrading the accuracy compared to the conventional Kalman filters. Moreover, the proposed method can directly estimate the electrical rotor position and speed without a back-electromotive force. The proposed Kalman filter for the sensorless control of a permanent magnet synchronous motor is verified through the simulation and experimentation. The performance of the proposed method is evaluated over a wide range of operations, such as forward and reverse rotations in low and high speeds including the detuning parameters.