• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.139-148
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• 1997

본 논문에서는 비선형 마찰이 존재하는 조준경 안정화 시스템에 대해서 마찰력 보상과 성능개선을 위한 신경망제어기의 설계방법을 제시한다. 제안한 신경망제어기는 비례, 적분, 진상(PI/LEAD) 제어기와 신경회로망과의 병렬로 구성되며, 제어 목적은 비선형 마찰과 외란이 존재하여도 안정거울의 각속도 추적성능과 안정화 성능의 향상에 있다. 신경회로망의 입력으로 안정거울의 각속도 추적오차와 추적오차의 적분, 제어입력이 필터를 통과한 신호가 사용되며, 신경호로망은 간접학습구조에 의해 학습된다. 조준경 시스템의 비선형 마찰력인 쿨롱마찰력의 크기가 외부환경에 따라 변하는 경우와 시스템으로 외란이 인가되는 경우에 대하여도 제안한 병렬제어기는 기존의 PI/LEAD 제어기보다 추적과 안정화 성능면에서 우수함을 컴퓨터 모의 실험으로 확인한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.71-76
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• 2023

This paper studied a method of attenuating nonlinear noise using a Wiener filter of a neural network structure in an acoustic noise attenuator. This system improves nonlinear noise attenuation performance with a deep learning algorithm using a neural network Wiener filter instead of using a conventional adaptive filter. A voice is estimated from a single input voice signal containing nonlinear noise using a 128-neuron, 8-neuron hidden layer and an error back propagation algorithm. In this study, a simulation program using the Keras library was written and a simulation was performed to verify the attenuation performance for nonlinear noise. As a result of the simulation, it can be seen that the noise attenuation performance of this system is significantly improved when the FNN filter is used instead of the Wiener filter even when nonlinear noise is included. This is because the complex structure of the FNN filter expresses any type of nonlinear characteristics well.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.454-457
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• 2011

본 논문에서는 국내에서 아직 기준이 마련되지 않은 제진설계에 대한 접근을 소개하였다. ASCE 7-05 기준에 근거하여 국내 5층 규모의 철근콘크리트 신축 건물에 제진 설계를 수행하였다. 우리나라의 현행 기준을 만족하면서 효과적인 제진 시스템 설계를 위한 방법을 소개한다. ASCE 7-05 기준에서는 제진 구조물 해석 시 부재력이 공칭강도의 1.5배를 초과하지 않은 경우 경계비선형 해석을 허용하고 있다. 이 때의 제진 설계 프로세스는 기존의 중력하중 및 등가정적하중의 75%에 의한 단면을 가정하여 부재설계를 실시하고, 선형 시간이력 해석을 통해 제진장치 및 가새를 설계한다. 이후 우리나라 실정에 맞도록 보정된 인공 지진파를 입력하여 경계비선형 해석을 실시하고, 밑면 전단력 및 층간변위 등의 만족여부를 검토한다. 이 때 목표성능을 완전탄성설계 또는 유사탄성설계로 정하여 목표성능을 만족하는지도 검토하여야 한다. 본 논문에 적용한 신축 건물은 유사탄성 설계를 위해 경계비선형 해석을 실시하였고, 가장 효과적인 제진 설계를 위해 댐퍼의 종류, 설치방법, 개수, 변위 증폭비 등을 변수로 한 case study를 진행하였다. 해석 결과 목표성능을 만족하는 범위 내에서 가장 효과적인 제진 설계는 점성댐퍼, 이층 토글형태, 증폭비 2.0, 총 8개의 댐퍼를 설치하는 것으로 나타났다.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.405-410
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• 2002

In this paper, fuzzy system modeling using new hierarchical structure is suggested for the complex and uncertain system. The proposed modeling technique Is to decompose the fuzzy rule base structure into the above-rule base and the sub-rule base. By applying hierarchical fuzzy rules, they can be used efficiently and logically. Also, hieratical fuzzy rules can improve the accuracy and the transparency of structure in the fuzzy system. The genetic algorithm is applied for optimization of the parameters and the structure of the fuzzy rules. To show the effectiveness of the proposed method, fuzzy modeling of the complex nonlinear system is provided.

• Journal of IKEEE
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• v.13 no.1
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• pp.30-35
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• 2009

A new controller which can achieve the asymptotic tracking is proposed for the nonlinear system having a uncertainty in the input coefficient. A high gain observer is used to estimate the state variables when the nonlinear system has a modeling uncertainty. A variable structure control is used to achieve an asymptotic tracking, while ultimate boundness was achieved in the previous work. A Lyapunov analysis is used to justify the our proposal. The performance of proposed method is demonstrated via simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.88-95
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• 2006

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They we difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.1-10
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• 2007

This paper presents a direct nonlinear multivariable self-tuning PID controller using neural network which adapts to the changing parameters of the nonlinear multivariable system with noises and time delays. The nonlinear multivariable system is divided linear part and nonlinear part. The linear controller are used the self-tuning PID controller that can combine the simple structure of a PID controllers with the characteristics of a self-tuning controller, which can adapt to changes in the environment. The linear controller parameters are obtained by the recursive least square. And the nonlinear controller parameters are achieved the through the Back-propagation neural network. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation results are presented to adapt the nonlinear multivariable system with noises and time delays and with changed system parameter after a constant time. The proposed PID type nonlinear multivariable self-tuning method using neural network is effective compared with the conventional direct multivariable adaptive controller using neural network.

• Journal of Korean Society of Steel Construction
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• v.19 no.6
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• pp.633-642
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• 2007

Although the Load and Resistance Factor Design (LRFD) method is an advanced design approach, it does not accurately capture the interaction between individual members and structural system. A nonlinear inelastic analysis for the entire structure is required to solve this problem. According to many design codes of advanced countries, a nonlinear inelastic analysis can be applied to predict the structural behavior and strength reasonably. In this study, an LRFD design method using practical nonlinear inelastic analysis was proposed. Design examples using the proposed method waspresented, and the economical efficiency and adequacy of the proposed method was investigated by comparing the design results with that of the AISC-LRFD. It has been consequently demonstrated that the proposed method can reduce the construction cost through savings in steel.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.97-105
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• 1996

In this paper, an adaptive model predictive controller for nodinear processes using fuzzy model is proposed. Adaptive structure is implemented by recursive fuzzy modeling. The model and control law can be obtained the same as GPC, because the consequent parts of the fuzzy model comprise linear equations of input and output variables. The proposed Adaptive fuzzy model predictive controller (AFMPC) controls nonlinear process well due to the intrinsic nonlinearity of the fuzzy model. When AFMPC's output is variation in the process control input, it maintains zero steady-state offset for a constant reference input and has superior performance. The properties and performance of the proposed control scheme were examined with nonlinear plant by simulation.

• Journal of Korean Society of Steel Construction
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• v.15 no.6 s.67
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• pp.661-672
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• 2003

The advanced analysis and optimal design of semi-rigid frame were presented. Advanced analysis can predict the combined nonlinear effects of connection, geometry, and material on the behavior and strength of semi-rigid frames. The Kishi-Chen power model was used to describe the nonlinear behavior of semi-rigid connections. Geometric nonlinearity was determined using stability functions. On the other hand, material nonlinearity was determined using the Column Research Council (CRC) tangent modulus and parabolic function. The direct search method proposed by Choi and Kim was used as optimization technique. The member with the largest unit value evaluated using the LRFD interaction equation was replaced one by one with an adjacent larger member selected from the database. The objective function was assumed as the weight of steel frame, with the constraint functions accounting for load-carrying capacities, deflections. inter-story drifts, and ductility requirement. Member sizes determined by the proposed method were compared with those derived using the conventional LRFD method.