• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.85.4-85
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• 2001

A learning controller is presented for repetitive walking motion of biped robot. The learning control scheme learns the approximate inverse dynamics input of biped walking robot and uses the learned input pattern to generate an input profile of different walking motion from that learnt. In the learning controller, the PID feedback controller takes part in stabilizing the transient response of robot dynamics while the feedforward learning controller plays a role in computing the desired actuator torques for feedforward nonlinear dynamics compensation in steady state. It is shown that all the error signals in the learning control system are bounded and the robot motion trajectory converges to the desired one asymptotically. The proposed learning control scheme is ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.151.3-151
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• 2001

A design of PI controller to be used to control the first-order lag plus dead time process, such as a flow process, by the coefficient diagram method (CDM) is investigated. The factor of the dead time of process is first approximated to be the first-order by the Pade approximation. The response of the flow control system designed by CDM satisfy both transient and steady state specifications. However, the transient response generally still has long rise time. In order to improve the speed of the system response, a feedforward controller (FFC) is added into the PI control system. The structure of the FFC is a phase lead structure with two designed parameters and one derivative time obtained from the reaction curve of the flow process ...

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.211-216
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• 2015

Recently, because of the growth in the leisure industry and interest in health, the demand for bicycles has increased. In this research, considering the vertical load on a bike frame under static state conditions, the deflection and mass of the bike frame were minimized by satisfying the service condition and performing optimization. The thickness of the bicycle-frame tube was set to a design variable, and its sensitivity was confirmed by an analysis of means (ANOM). To optimize the solution, a response-surface-method (RSM) model was constructed using D-Optimal and central composite design(CCD). The optimization was performed using a non-dominant sorting genetic algorithm (NSGA-II), and the optimal solution was verified by finite-element analysis.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.3
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• pp.198-205
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• 2006

The necessity of nondestructively inspecting austenitic steels, fiber-reinforced composites, and other inherently anisotropic materials has stimulated considerable interest in developing beam models for anisotropic media. The properties of slowness surface playa key role in the beam models based on the paraxial approximation. In this paper, we apply a modular multi-Gaussian beam (MMGB) model to study the effects of material anisotropy on ultrasonic beam profile. It is shown that the anisotropic effects of beam skew and excess beam divergence enter into the MMGB model through parameters defining the slope and curvature of the slowness surface. The overall beam profile is found when the quasilongitudinal(qL) beam propagates in the symmetry plane of transversely isotropic austenitic steels. Simulation results are presented to illustrate the effects of these parameters on ultrasonic beam diffraction and beam skew. The MMGB calculations are also checked by comparing the anisotropy factor and beam skew angle with other analytical solutions.

• KCI Concrete Journal
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• v.13 no.1
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• pp.11-17
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• 2001

The purpose of this state-of-the-art paper is to explore several important methods thor obtaining the equivalent loads in prestressed concrete structures. and to clarify the theoretical basis and implied assumptions of each method. The method devised in this stuffily include the use of curvature of tendon, characteristics of primary moment, self-equilibrium condition and linear segments approximation of tendon. It is shown that equivalent loading system it not uniquely determined depending on the approach adopted to calculate the equivalent loads. Self-equilibrium conditions of the equivalent loading system are carefully discussed. Numerical examples are presented to show the differences among the methods arid results of the approximations in each method explicitly.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.54-63
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• 1993

This paper proposes a method for improving the performances of the neural network for optimization by an optimal estimation of initial states. The optimal initial state that leads to the global minimum is estimated by using the stochastic approximation. And then the update rule of Hopfield model, which is the high speed deterministic algorithm using the steepest descent rule, is applied to speed up the optimization. The proposed method has been applied to the tavelling salesman problems and an optimal task partition problems to evaluate the performances. The simulation results show that the convergence speed of the proposed method is higher than conventinal Hopfield model. Abe's method and Boltzmann machine with random initial neuron output setting, and the convergence rate to the global minimum is guaranteed with probability of 1. The proposed method gives better result as the problem size increases where it is more difficult for the randomized initial setting to give a good convergence.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.852-857
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• 2008

A new adaptive neuro-control algorithm for a SISO strict-feedback nonlinear system is proposed. All the previous adaptive neural control algorithms for strict-feedback nonlinear systems are based on the backstepping scheme, which makes the control law and stability analysis very complicated. The main contribution of the proposed method is that it demonstrates that the state-feedback control of the strict-feedback system can be viewed as the output-feedback control problem of the system in the normal form. As a result, the proposed control algorithm is considerably simpler than the previous ones based on backstepping. Depending heavily on the universal approximation property of the neural network (NN), only one NN is employed to approximate the lumped uncertain system nonlinearity. The Lyapunov stability of the NN weights and filtered tracking error is guaranteed in the semi-global sense.

• Smart Structures and Systems
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• v.19 no.4
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• pp.431-439
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• 2017

This investigation is aimed to develop a model of experimental-computation determination of a support moment of a cantilever beam loaded with concentrated force at its end including the optimal choice of coordinates of deflection data points and parameters of transformation of deflection data in case of insufficient accuracy of the assignment of initial parameters (support settlement, angle of rotation of the bearing section) and cantilever beam length. The influence of distribution and characteristics of sensors on the cantilever beam on the accuracy of determining the support moment which improves in the course of transition from the uniform distribution of sensors to optimal non-uniform distribution is shown. On the basis of the theory of inverse problems the method of transformation reduction at numerical differentiation of deflection functions has been studied. For engineering evaluation formulae of uncertainty estimate to determine a support moment of a cantilever beam at predetermined uncertainty of measurements using sensors have been obtained.

• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.427-442
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• 2011

Calcium is a vital second messenger for signal transduction in neurons. Calcium plays an important role in almost every part of the human body but in neuronal cytosol, it is of utmost importance. In order to understand the calcium signaling mechanism in a better way a finite element model has been developed to study the flow of calcium in two dimensions with time. This model assumes EBA (Excess Buffering Approximation), incorporating all the important parameters like time, association rate, influx, buffer concentration, diffusion constant etc. Finite element method is used to obtain calcium concentration in two dimensions and numerical integration is used to compute effect of time over 2-D Calcium profile. Comparative study of calcium signaling in two dimensions with time is done with other important physiological parameters. A MATLAB program has been developed for the entire problem and simulated on an x64 machine to compute the numerical results.

• Proceeding of KASS Symposium
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• 2005.05a
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• pp.125-132
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• 2005

Membrane structures, a kind of lightweight soft structural system, are used for spatial structures. The material property of the membrane has strong axial stiffness, but little bending stiffness. The design procedure of membrane structures are needed to do shape finding, stress-deformation analysis and cutting pattern generation. In shape finding, membrane structures are unstable structures initially. These soft structures need to be introduced initial stresses because of its initial unstable state, and it happens large deformation phenomenon. And also there are highly varied in their size, curvature and material stiffness. So, the approximation inherent in cutting pattern generation methods is quite different. Therefore, in this study, to find the structural shape after large deformation caused by Initial stress, we need the shape analysis considering geometric nonlinear ten And the geodesic line on surface of initial equilibrium shape and the cutting pattern generation using the geodesic line is introduced.