• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.53-60
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• 2018

In this paper, we described the unknown parameter identification using Dual Extended Kalman Filter for precise control of 2-link manipulator. 2-link manipulator has highly non-linear characteristic with changed parameter thought tasks. The parameter kinds of mass and inertia of system is important to handle with the manipulator robustly. To solve the control problem by estimating the state and unknown parameters of the system through the proposed method. In order to verify the performance of proposed method, we simulate the implementation using Matlab and compare with results of RLS algorithm. At the results, proposed method has a better performance than those of RLS and verify the estimation performance in the parameter estimation.

• Advances in aircraft and spacecraft science
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• v.7 no.1
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• pp.1-17
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• 2020

In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the changes in the control forces and moments, system dynamics will change too, leading to the failure detection process being encountered with difficulty. To this purpose, an equivalent aerodynamic model is proposed to express the dynamics of the vehicle, and the health of each fin is monitored by the value of a parameter which is estimated using an adaptive robust filter. The proposed method detects and isolates fins damages in a few seconds with good accuracy.

• Aerospace Engineering and Technology
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• v.8 no.1
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• pp.58-65
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• 2009

The paper identifies noise characteristics of a nonliner image sensor model which reflects a saturation effect of each detector pixel and extends the result to estimate an image SNR (Signla-to-Noise Ratio) distribution over all the pixels in a detector. In particular, nonlinearity of a pixel is studied from two perspectives of including asymmetry of a noise PDF (Probability Distribution Function) and enhancing a pixel SNR value, in comparison to a linear model. It is noted that the proposed image SNR distribution function is useful to effectively select new optimal operation parameter values: an integration time and an pixel-summing number, even after a launch campaign, assuming sensor gain degradation in orbit or inevitable modification of some operation parameter values due to space contingency.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1008-1027
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• 2014

An electric scooter with a V-belt continuously variable transmission (CVT) driven by a permanent magnet synchronous motor (PMSM) has a lot of nonlinear and time-varying characteristics, and accurate dynamic models are difficult to establish for linear controller designs. A PMSM servo-drive electric scooter controlled by a novel hybrid modified recurrent Legendre neural network (NN) control system is proposed to solve difficulties of linear controllers under the occurrence of nonlinear load disturbances and parameters variations. Firstly, the system structure of a V-belt CVT driven electric scooter using a PMSM servo drive is established. Secondly, the novel hybrid modified recurrent Legendre NN control system, which consists of an inspector control, a modified recurrent Legendre NN control with an adaptation law, and a recouped control with an estimation law, is proposed to improve its performance. Moreover, the on-line parameter tuning method of the modified recurrent Legendre NN is derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, two optimal learning rates for the modified recurrent Legendre NN are derived to speed up the parameter convergence. Finally, comparative studies are carried out to show the effectiveness of the proposed control scheme through experimental results.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.855-864
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• 2011

In this paper, a nonlinear controller based on adaptive back-stepping method is proposed for high performance operation of IPMSM(Interior Permanent Magnet Synchronous Motor). First, in order to improve the performance of speed tracking a nonlinear back-stepping controller is designed. Since it is difficult to control the high performance driving without considering parameter variation, a parameter estimator is included to adapt to the variation of load torque in real time. In addition, for the efficiency of power consumption of the motor, controller is designed to operate motor with minimum current for maximum torque. The proposed controller is applied through simulation to the a 2-hp IPMSM for the angular velocity reference tracking performance and load torque volatility estimation, and to test the MTPA(Maximum Torque per Ampere) operation in constant torque operation region. The result verifies the efficacy of the proposed controller.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1679-1688
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• 1990

The method of nonlinear parameter estimation(NPE), which is a statistical and an inverse method, is used to estimate the thermal diffusivity of the porous insulation material. In order to apply the NPE method for measuring the thermal diffusivity, and algorithm for programing suitable to IBM personal computer is established, and is studied the statistical treatment of experimental data and theory of estimation. The experimental data obtained by discrete measurement using a constant heat flux technique are used to find the boundary conditions, initial conditions, and the thermal diffusivity, and then the final values are compared with the values obtained by some different methods. The results are presented as follows:(1) NPE method is used to establish the estimation of the thermal diffusivity and compared results with experimental output shows, that this method can be applicable to define the thermal diffusivity without considering hear flux types. (2) Because of all of the temperatures obtained by the discrete measurement on each steps of time are used to estimate the thermal diffusivity. Although some error in the temperature measurements of temperature are included in estimating process, its influences on the final value are minimzed in NPE method. (3) NPE method can reduce the experimental time including the time of data collecting in a few minutes and can take smaller specimen compared with steady state method. If the tube-type furnace is used, also the adjusting time of surrounding temperature can be reduced.

• Computers and Concrete
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• v.16 no.1
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• pp.99-123
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• 2015

In this study, structural vulnerability of reinforced concrete moment resisting frames (RC-MRFs) by considering the Iran-specific characteristics is investigated to manage the earthquake risk in terms of multicomponent seismic excitations. Low and medium rise RC-MRFs, which constitute approximately 80-90% of the total buildings stock in Iran, are focused in this fragility-based assessment. The seismic design of 3-12 story RC-MRFs are carried out according to the Iranian Code of Practice for Seismic Resistant Design of Buildings (Standard No. 2800), and the analytical models are formed accordingly in open source nonlinear platforms. Frame structures are categorized in three subclasses according to the specific characteristics of construction practice and the observed seismic performance after major earthquakes in Iran. Both far and near fields' ground motions have been considered in the fragility estimation. An optimal intensity measure (IM) called Sa, avg and beta probability distribution were used to obtain reliable fragility-based database for earthquake damage and loss estimation of RC buildings stock in urban areas of Iran. Nonlinear incremental dynamic analyses by means of lumped-parameter based structural models have been simulated and performed to extract the fragility curves. Approximate confidence bounds are developed to represent the epistemic uncertainties inherent in the fragility estimations. Consequently, it's shown that including vertical ground motion in the analysis is highly recommended for reliable seismic assessment of RC buildings.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.174-180
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• 1996

The friction is one of the nonlinearities to be considered in the precise position control of a system which has electromechanical components. The friction has complicated nonlinear characteristics and depends on the velocity, the position and the time. The conventional fixed friction compensator and the controller based on linear control theory may cause the steady state position error or oscillation. The plant to be controlled in this study is a positioning system with a linear brushless DC motor(LBLDCM). The system behaves like a 4th-order model including the compliance and the friction. In this study, the plant model is simplified to a 2nd-order model to reduce the computation in on- line estimation. Also, to reduce the computation time, only the friction is estimated on-line while the mass and the viscous damping coefficient are fixed to the values obtained from off-line estimation. The validity of the proposed scheme is illustrated with the computer simulation and the experiment where the friction is compensated by using the estimation.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.186-192
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• 1999

This paper introduces a study of a method for the forward kinematic analysis, which finds the 6 DOF motions and velocities from the given six cylinder lengths in the Stewart platform. From the viewpoints of kinematics, the solution for the inverse kinematic is easily found by using the vectors of the links which are composed of the joint coordinates in base and plate frames, to act contrary to the serial manipulator, but forward kinematic is difficult because of the nonlinearity and complexity of the Stewart platform dynamic equation with the multi-solutions. Hence we, first in this study, introduce the linear estimator using the Luenberger's observer, and the estimator using the nonlinear measured model for the forward kinematic solutions. But it is difficult to find the parameter of the design for the estimation gain or to select the estimation gain and the constant steady state error exists. So this study suggests the estimator with the estimation gain to be learned by the neural network with the structure of multi-perceptron and the learning method using back propagation and shows the estimation performance using the simulation.

• Journal of Power Electronics
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• v.16 no.1
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• pp.238-248
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• 2016

The state-of-charge (SOC) and state-of-health (SOH) estimation of batteries play important roles in managing batteries for automotive applications. However, an accurate state estimation of a battery is difficult to achieve because of certain factors, such as measurement noise, highly nonlinear characteristics, strong hysteresis phenomenon, and diffusion effect of batteries. In certain vehicular applications, such as idle stop-start systems (ISSs), significant errors in SOC/SOH estimation may lead to a failure in restarting a combustion engine after the shut-off period of the engine when the vehicle is at rest, such as at a traffic light. In this paper, a dual extended Kalman filter algorithm with a dynamic equivalent circuit model of a lead-acid battery is proposed to deal with this problem. The proposed algorithm adopts a battery model by taking into account the hysteresis phenomenon, diffusion effect, and parameter variations for accurate state estimations of the battery. The validity of the proposed algorithm is verified through experiments by using an absorbed glass mat valve-regulated lead-acid battery and a battery sensor cable for commercial ISS vehicles.