• Proceedings of the KIEE Conference
• /
• 2000.11a
• /
• pp.39-42
• /
• 2000

In stressed power system, due to the presence of increased nonlinearity and the existence of nonlinear modal interactions, there exist some limitations to the use of conventional linear system theory to identify the optimum sites for controller. This paper proposes an approach to identify the optimum sites for controller using the method of normal forms. In this paper nonlinear participation factor and coupling factor are proposed as a measures of identification of optimum sites for controller and a selection procedure is also proposed. The proposed procedure is applied to the 10-generator New England System and the KEPCO System in the year of 2010 to illustrate its capabilities.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.507-509
• /
• 1999

In this paper, we propose a new fuzzy model identification method that can yield a successful fuzzy rule base for fundamental approximations. The method in this paper uses a set of input-output data and is based on a hybrid messy genetic algorithm (mGA) with a fine-tuning scheme. The mGA processes variable-length strings, while standard GAs work with a fixed-length coding scheme. For successfully identifying a complex nonlinear system, we first use the mGA, which coarsely optimizes the structure and the parameters of the fuzzy inference system, and then the gradient descent method which tine tunes the identified fuzzy model. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its application to a nonlinear approximation.

• Structural Engineering and Mechanics
• /
• v.6 no.8
• /
• pp.857-870
• /
• 1998

This paper deals with a special class of inverse problems in discrete structural plasticity involving the identification of elastic limits and hardening moduli on the basis of information on displacements. The governing equations lead naturally to a special and challenging optimization problem known as a Mathematical Program with Equilibrium Constraints (MPEC), a key feature of which is the orthogonality of two sign-constrained vectors or so-called "complementarity" condition. We investigate numerically the application of two simple algorithms, both based on the use of the general purpose nonlinear programming code CONOPT accessed via the GAMS modeling language, for solving the suitably reformulated problem. Application is illustrated by means of two numerical examples.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.558-563
• /
• 1992

In this paper an identification of nonlinear continuous systems by using neural network is considered. The nonlinear continuous system is identified by two steps. At first, a linear approximate model of the continuous system with nonlinearity is obtained by IIR filtering approach. Then the modeling error due to the nonlinearity is reduced by a neural network compensator. The teaching signals to train the neural network is gotten by smoothing the measurement data corrupted by noise. An illustrative example is given to demonstrate the effectiveness of the proposed approach.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.5 no.2
• /
• pp.67-72
• /
• 2001

대상으로 하는 시스템의 입출력신호에 근거하여, 시스템의 수학적 모델을 결정하는 것을 총칭하여 시스템식별이라 한다. 본 논문에서는 지진응답 관측치를 입출력신호로 하여 조건부대치를 최적치로 판단하는 비선형근사필터법을 사용한 건축구조물의 지진응답추정 및 파라미터식별에 관하여 논한다. 비선형근사필터법에 의한 건축구조물식별의 유효성의 적용성을 판단하기 위해, 진동대를 사용하여 강구조시험체의 진동실험을 행하고 결과적으로 얻어진 시험체의 수학적 모델에 대한 지진응답 수치해석결과와 진동실험에서의 관측기록을 비교하여 본 식별법의 타당성을 보인다.

• Smart Structures and Systems
• /
• v.18 no.5
• /
• pp.839-864
• /
• 2016

This paper presents an efficient method for updating the structural finite element model. Model updating is performed through minimizing the difference between the recorded acceleration of a real damaged structure and a hypothetical damaged one. This is performed by updating physical parameters (module of elasticity in this study) in each step using iterative process of modified nonlinear conjugate gradient (M-NCG) and modified Broyden-Fletcher-Goldfarb-Shanno algorithm (M-BFGS) separately. These algorithms are based on sensitivity analysis and provide a solution for nonlinear damage detection problem. Three illustrative test examples are considered to assess the performance of the proposed method. Finally, it is demonstrated that the proposed method is satisfactory for detecting the location and ratio of structural damage in presence of noise.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.720-723
• /
• 1997

The characteristics of ball and beam system using fuzzy inference technique can be described by fuzzy modeling. Therefore, this paper introduces a technique for fuzzy structure identification of nonlinear Input-output relation- ship using an adaptive fuzzy inference system. And the simulation result using adaptive fuzzy inference technique shows its effectiveness for fuzzy structure identification of nonlinear system.

• Computers and Concrete
• /
• v.1 no.2
• /
• pp.131-150
• /
• 2004

We present in this work a coupled phenomenological chemo-mechanical model that represents the degradation of concrete-like materials. The chemical behaviour is described by the nowadays well known simplified calcium leaching approach. And the mechanical damage behaviour is described by a continuum damage model which involves the gradient of the damage quantity. The coupled nonlinear problem at hand is addressed within the context of the finite element method. For the equation governing the calcium dissolution-diffusion part of the problem, special care is taken to treat the highly nonlinear calcium conductivity and solid calcium functions. The algorithmic design is based on a Newton-type iterative scheme where use is made of a recently proposed relaxed linearization procedure. And for the equation governing the damage part of the problem, an augmented Lagrangian formulation is used to take into account the damage irreversibility constraint. Finally, numerical simulations are compared with experimental results on cement paste.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.05a
• /
• pp.495-500
• /
• 2003

The vibration of a flexible cantilever tube with nonlinear constraints when it is subjected to flow internally with fluids is examined by experiment and theoretical analysis. These kind of studies have often been performed that finds the existence of chaotic motion. In this paper, the important parameters of the system leading to such a chaotic motion such as Young's modulus and coefficient of viscoelasticity in tube material are discussed. The parameters are investigated by means of a system identification so that comparisons are made between numerical analysis using the parameters of a handbook and the experimental results. The chaotic region led by several period-doubling bifurcations beyond the Hopf bifurcation is also re-established with phase portraits and bifurcation diagram so that one can define optimal parameters for system design.

• Journal of the Institute of Convergence Signal Processing
• /
• v.4 no.3
• /
• pp.41-48
• /
• 2003

This paper presents an indirect adaptive neuro controller using modified chaotic neural networks(MCNN) for nonlinear dynamic system. A modified chaotic neural networks model is presented for simplifying the traditional chaotic neural networks and enforcing dynamic characteristics. A new Dynamic Backpropagation learning method is also developed. The proposed MCNN paradigm is applied to the system identification of a MIMO system and the indirect adaptive neuro controller. The simulation results show good performances, since the MCNN has robust adaptability to nonlinear dynamic system.