• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.688-696
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• 2017

This paper presents an integrated roll-pitch-yaw autopilot using an equivalent based sliding mode control for skid-to-turn nonlinear time-varying missile system with lumped disturbances in its six-equations of motion. The considered missile model are developed to integrate the model uncertainties, external disturbances, and parameters perturbation as lumped disturbances. Moreover, it considers the coupling effect between channels, the variation of missile velocity and parameters, and the aerodynamics nonlinearity. The presented approach is employed to achieve a good tracking performance with robustness in all missile channels simultaneously during the entire flight envelope without demand of accurate modeling or output derivative to avoid the noise existence in the real missile system. The proposed autopilot consisting of a two-loop structure, controls pitch and yaw accelerations, and stabilizes the roll angle simultaneously. The Closed loop stability is studied. Numerical simulation is provided to evaluate performance of the suggested autopilot and to compare it with an existing autopilot in the literature concerning the robustness against the lumped disturbances, and the aforesaid considerations. Finally, the proposed autopilot is integrated in a six degree of freedom flight simulation model to evaluate it with several target scenarios, and the results are shown.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.190-196
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• 2006

In this paper, the nonlinear damping force model is made to identify the properties of the ER damper using higher order spectrum. The higher order spectral analysis is used to investigate the nonlinear frequency coupling phenomena with the damping force signal according to the sinusoidal excitation of the damper. Also, this paper presents an inverse model of the ER damper, i.e., the model can predict the required voltage so that the ER damper can produce the desired force for the requirement of vibration control of vehicle suspension systems. The inverse model has been constructed by using piecewise linear damping force model. In this paper, the fuzzy logic control based on heuristic knowledge is combined with the skyhook control. And it is simulated for a quarter car model. The acceleration of the sprung mass is included in the premise part of the fuzzy rules to reduce the vertical acceleration RMS value of the sprung mass. Then scaling factors and membership functions are tuned using genetic algorithm to obtain optimal performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.3
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• pp.31-36
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• 2006

In this study, nonlinear static aeroelastic analysis system for a high-aspect-ratio wing are developed using the transonic small disturbance (TSD) and large deflection beam theory and validated. For the coupling between fluid and structure, the transformation of displacement from the structural mesh to aerodynamic one is performed by the shape function of the beam finite element and the inverse transformation of force by work equivalent load concept. Also, for the static aeroelastic analysis of the wing the use of TSD aerodynamics are justified. The validation of the system includes one of the efficient transformation methods of force and displacement.

• Multiscale and Multiphysics Mechanics
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• v.1 no.2
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• pp.143-156
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• 2016

Reinforced concrete (RC) structures require advanced analysis techniques for better estimation of their seismic responses, especially in the case of exhibiting complex three-dimensional coupling of torsional and flexural behaviors. This study focuses on validating a numerical approach for evaluating the seismic response of a three-dimensional unsymmetrical RC structure through the participation in the SMART 2013 international benchmark program. The benchmark program provides material properties, detailed drawings of the RC structure, and input ground motions for the seismic response evaluation. In this study, nonlinear constitutive models of concrete and rebar were formed and local tests were conducted to verify the constitutive models in finite element analysis. Elastic calibration of the finite element model of the SMART 2013 RC structure was performed by comparing numerical and experimental results in modal and linear time history analyses. Using the calibrated model, nonlinear earthquake analysis and seismic fragility analysis were performed to estimate the behavior and vulnerability of the RC structure with various ground motions.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.387-394
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• 2000

The nonlinear modal interaction of an autoparametric system under a broadband random excitation is investigated. The specific system examined is an autoparametric vibration absorber with internal resonance, which is typical of many common structural configurations. By means of Gaussian closure scheme the dynamic moment equations explaining the random responses of the system are reduced to a system of autonomous ordinary differential equations of the first and second moments. In view of equilibrium solutions of this system and their stability we examine the system responses. We could not find the destabilizing effect of damping, which was reported in References (18) and (20). The saturation phenomenon, which is well known in deterministic nonlinear system, did not take place lot this system subject to broadband random excitation.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.6
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• pp.23-31
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• 2010

It is necessary to develop reliable but simple analytical models to predict the nonlinear response of reinforced concrete wall structures. In this study, experimental results on the cyclic reversed lateral behaviors of reinforced concrete shear wall assemblages are simulated analytically by using the wall, beam, and column models available in the PERFORM 3D program. Through the comparison of experimental and analytical results, the reliability and limitations of the analysis are evaluated. In addition, the information, which could not be obtained experimentally, such as the internal flow of force, the contribution of the flange walls, and the resisting mechanism of the walls with the contribution of the coupling beam, is provided.

• Journal of the Korean Solar Energy Society
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• v.23 no.3
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• pp.37-44
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• 2003

This paper presents the modeling and analysis of V47-660 kW wind turbine generation system(WTGS) in Jeju wind farm using Psim program. Generally, WTGS is composed of complicated machinery. So it is very difficult to present the mathematic model. This means that WTGS has a nonlinear system. Using the real output data from V47 WTGS for one year, it is simply possible to express the rotor and gear coupling system as a torque generator according to wind speed. Also, the modeling of electrical system can be able to present using the data sheet from the company. To analyze the proposed method, results of computer simulation using Psim program are presented to support the discussion.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.352-361
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• 2018

This paper proposes a sensing system of the Halbach array permanent magnet spherical motor(PMSM). The rotor position can be obtained by solving three rotation angles, which revolves around 3 reference axes of the stator. With the development of 3-D hall sensor, the position identification problem of the Halbach array PMSM based on rotor magnetic field is studied in this paper. A nonlinear and serious coupling relationship between the rotation angles and the measured magnetic flux density is established on the basis of the rotation transformation theory and the magnetic field model. In order to get rid of the influence on position detection caused by the harmonics of rotor magnetic field and the stator coil magnetic field, a sensor location combination scheme is proposed. In order to solve the nonlinear equation fast and accurately, a new position solution algorithm which combines the merits of gradient projection and particle swarm optimization(PSO) is presented. Then the rotation angles are obtained and the rotor position is identified. The validity of the sensing system is verified through the simulation.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.225-227
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed artificial intelligent-PI(AIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.