• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.99-106
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• 2003

A new reconfigurable model following flight control method based on direct adaptive scheme is presented. Using the timescale separation principle, both the inner-loop and the outer-loop states are controlled simultaneously. For the timescale separation assumption to be satisfied, the inner-loop model dynamics is set to be fast whereas the outer-loop model dynamics is set to be relatively slow. The stability and convergence of the proposed control law is proved by Lyapunov theorem. One of the merits of the proposed reconfigurable controller is that the FDI process and the persistent input excitation are not necessary, which is suitable for the flight control system. To evaluate the reconfiguration performance of the proposed control method, numerical simulation is performed using six degree-of-freedom nonlinear dynamics.

• Structural Engineering and Mechanics
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• v.64 no.4
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• pp.495-504
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• 2017

This paper proposes a new direct numerical integration algorithm for solving equation of motion in structural dynamics problems with nonlinear stiffness. The new implicit method's degree of accuracy is higher than that of existing methods due to the higher order of the acceleration. Two parameters are defined, leading to a new family of unconditionally stable methods, which helps to take greater time steps in integration and eliminate concerns about the duration of solving. The method developed can be utilized for a number of solid plane finite elements, examples of which are given to compare the proposed method with existing ones. The results indicate the superiority of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.14-19
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• 1993

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.1
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• pp.54-62
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• 1994

The expanding technique of the Stochastic Finite Element Method(SFEM) is proposed in this paper for adapting direct integration methods in stochastical dynamic analysis of structures. Grafting the direct integration methods and the SFEM together, one can deal with nonlinear structures and nonstationary process problems without any restriction. The stochastical central diffrence and stochastic Houbolt methods are introduced to show the expanding technique, and their adaptabilities are discussed. Results computed by the proposed method (the Stochastic Finite Element Method in Dynamics: SFEMD) for two degree-of-free- dom system are compared with those obtained by Monte Carlo Simulation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.474-483
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• 1996

In this paper, as a part of the method improving stability, the load-flow calculation in D.C. power system and the models for stability analysis are studied with A.C-D.C. interconnected power systems transmission performed. Moreover, the theory is established in relation to each control method of D.C. power systems. Then the stability of A.C-D.C.interconnected power systems is compared and considered by the way of dividing the operating control method of the rectifier inverter converter into ACR-AVR, APR-A.gamma.R, A.alpha.R-ACR. The dynamics characteristic of terminal voltage, frequency, active-reactive power and rotor angle of the generator with disturbances and load fluctuations is considered. In addition, the characteristic of direct voltage, direct current, power and control systems. From this the comparative analysis of the direct current control method, the possibility of the stability analysis of A.C.-D.C. interconnected power system is considered. (author). refs., figs., tabs.

• Tribology and Lubricants
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• v.29 no.5
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• pp.318-323
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• 2013

Overheating in electrical motors results in detrimental effects such as degradation of the insulation materials, demagnetization of magnets, increases in Joule losses, and decreases in motor efficiency and lifetime. Thus, it is important to find ways to dissipate heat from the motor and to keep the motor operating at its most efficient temperature. In this study, a new design to guide air flow through a given brushless direct current (BLDC) motor is developed and the design is analyzed, specifically by using computational fluid dynamics (CFD) simulations. The results showed that the temperature distribution in the three proposed models is lower than that in the original model, although the speed of the cooling fan in the original model reaches a very high value of $15{\times}10^3$ rpm. The results also showed that CFD can be effectively used to simulate the heat transfer of BLDC motors.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.124-129
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• 2002

This paper demonstrates that the largest Lyapunov exponent λ of recurrent neural networks can be controlled efficiently by a stochastic gradient method. An essential core of the proposed method is a novel stochastic approximate formulation of the Lyapunov exponent λ as a function of the network parameters such as connection weights and thresholds of neural activation functions. By a gradient method, a direct calculation to minimize a square error (λ - λ$\^$obj/)$^2$, where λ$\^$obj/ is a desired exponent value, needs gradients collection through time which are given by a recursive calculation from past to present values. The collection is computationally expensive and causes unstable control of the exponent for networks with chaotic dynamics because of chaotic instability. The stochastic formulation derived in this paper gives us an approximation of the gradients collection in a fashion without the recursive calculation. This approximation can realize not only a faster calculation of the gradient, but also stable control for chaotic dynamics. Due to the non-recursive calculation. without respect to the time evolutions, the running times of this approximation grow only about as N$^2$ compared to as N$\^$5/T that is of the direct calculation method. It is also shown by simulation studies that the approximation is a robust formulation for the network size and that proposed method can control the chaos dynamics in recurrent neural networks efficiently.

• 한국전산유체공학회:학술대회논문집
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• 2009.11a
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• pp.88-92
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• 2009

When exposed to uniform magnetic fields externally applied, paramagnetic particles acquire dipole moments and the induced moments interacting with each other lead to the formation of chainlike structures or clusters of particles aligned with the field direction. A direct simulation method, based on the Maxwell stress tensor and a fictitious domain method, is applied to solve flows with magnetic chains in simple shear flow. We assumed that the particles constituting the chains are paramagnetic, and inertia of both flow and magnetic particles is negligible. The numerical scheme enables us to take into account both hydrodynamic and magnetic interactions between particles in a fully coupled manner, enabling us to numerically visualize breakup and reformation of the chains by the combined effect of the external field and the shear flow. Simple shear flow with suspended magnetic chains is solved in a periodic domain for a given magnetic field. Dynamics of interacting magnetic chains is found to be significantly affected by a dimensionless parameter called the Mason number, the ratio of the viscous force to the magnetic force in the shear flow. The effect of particle area fraction on the chain dynamics is investigated as well.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.411-421
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• 2005

The development and implementation of an appropriate methodology for the accurate geometric description of track models is proposed in the framework of multibody dynamics and it includes the representation of the track spatial geometry and its irregularities. The wheel and rail surfaces are parameterized to represent any wheel and rail profiles obtained from direct measurements or design requirements. A fully generic methodology to determine, online during the dynamic simulation, the coordinates of the contact points, even when the most general three dimensional motion of the wheelset with respect to the rails is proposed. This methodology is applied to study specific issues in railway dynamics such as the flange contact problem and lead and lag contact configurations. A formulation for the description of the normal contact forces, which result from the wheel-rail interaction, is also presented. The tangential creep forces and moments that develop in the wheel-rail contact area are evaluated using : Kalker linear theory ; Heuristic force method ; Polach formulation. The methodology is implemented in a general multibody code. The discussion is supported through the application of the methodology to the railway vehicle ML95, used by the Lisbon metro company.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.1
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• pp.37-45
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• 2022

It is well known that the Kano model measures customer satisfaction and classifies quality attributes into must-be, attractive as well as one-dimensional. The main purpose of this study is to investigate the dynamics of e-learning quality attributes by applying the proposed method using Kano's satisfaction index in the rapidly changing online learning environment. For this, the current study examined 27 e-learning quality attributes and conducted a comparative study using Kano's results obtained in 2013 and 2020. The result shows that the dynamics of quality attributes suggested by Kano(2001) is confirmed in the case of e-learning. The proposed approach shows better results in terms of Kano's direct classification method, and has potential application areas such as IPA(Importance-Performance Analysis) in the area of risk assemement. Some suggestions for better understanding of the proposed SI-DI diagram are also included in this study.