• Coupled systems mechanics
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• 제6권3호
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• pp.229-249
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• 2017

A new technique to mitigate irregular buildings with soil structure interaction (SSI) effect subjected to critical seismic waves is presented. The L-shape in plan irregular building for various reasons was selected, subjected to seismic a load which is a big problem for structural design especially without separation gap. The L-shape in plan building with different dimensions was chosen to study, with different rectangularity ratios and various soil kinds, to show the effect of the irregular building on the seismic response. A 3D building subjected to critical earthquake was analyzed by structural analysis program (SAP2000) fixed and with SSI (three types of soils were analyzed, soft, medium and hard soils) to find their effect on top displacement, base shear, and base torsion. The straining actions were appointed and the treatment of the effect of irregular shape under critical earthquake was made by using tuned mass damper (TMD) with different configurations with SSI and without. The study improve the success of using TMDs to mitigate the effect of critical earthquake on irregular building for both cases of study as fixed base and raft foundation (SSI) with different TMDs parameters and configurations. Torsion occurs when the L-shape in plan building subjected to earthquake which may be caused harmful damage. TMDs parameters which give the most effective efficiency in the earthquake duration must be defined, that will mitigate these effects. The parameters of TMDs were studied with structure for different rectangularity ratios and soil types, with different TMD configurations. Nonlinear time history analysis is carried out by SAP2000 with El Centro earthquake wave. The numerical results of the parametric study help in understanding the seismic behavior of L-shape in plan building with TMDs mitigation system.

• 제어로봇시스템학회논문지
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• 제8권2호
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• pp.126-135
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• 2002

The study is concerned with an approach to the design of new architectures of fuzzy neural networks and the discussion of comprehensive design methodology supporting their development. We propose an Adaptive Fuzzy Polynomial Neural Networks(APFNN) based on Fuzzy Neural Networks(FNN) and Self-organizing Networks(SON) for model identification of complex and nonlinear systems. The proposed AFPNN is generated from the mutually combined structure of both FNN and SON. The one and the other are considered as the premise and the consequence part of AFPNN, respectively. As the premise structure of AFPNN, FNN uses both the simplified fuzzy inference and error back-propagation teaming rule. The parameters of FNN are refined(optimized) using genetic algorithms(GAs). As the consequence structure of AFPNN, SON is realized by a polynomial type of mapping(linear, quadratic and modified quadratic) between input and output variables. In this study, we introduce two kinds of AFPNN architectures, namely the basic and the modified one. The basic and the modified architectures depend on the number of input variables and the order of polynomial in each layer of consequence structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the AFPNN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed AFPNN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• 대한조선학회논문집
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• 제60권3호
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• pp.155-164
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• 2023

About 75% of vessel collision accidents are caused by human error, which causes enormous economic loss, environmental pollution, and human casualties, thus research on automatic collision avoidance of vessels is being actively conducted. In addition, vessels must comply with the COLREGs rules stipulated by IMO when performing collision avoidance with other vessels in motion. In this study, the collision risk was calculated by estimating the position and velocity of other vessels through the Probabilistic Data Association Filter (PDAF) algorithm based on RADAR sensor data. When a collision risk is detected, we propose an event-triggered Nonlinear Model Predict Control (NMPC) algorithm that geometrically creates waypoints that satisfy COLREGs and follows them. To verify the proposed algorithm, simulations through MATLAB are performed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2393-2398
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• 2003

In this paper, we proposes a new fuzzy inference system for modeling nonlinear systems given input and output data. In the suggested fuzzy inference system, the number of fuzzy rules and parameter values of membership functions are automatically decided by using the kernel-based method. The kernel-based method individually performs linear transformation and kernel mapping. Linear transformation projects input space into linearly transformed input space. Kernel mapping projects linearly transformed input space into high dimensional feature space. The structure of the proposed fuzzy inference system is equal to a Takagi-Sugeno fuzzy model whose input variables are weighted linear combinations of input variables. In addition, the number of fuzzy rules can be reduced under the condition of optimizing a given criterion by adjusting linear transformation matrix and parameter values of kernel functions using the gradient descent method. Once a structure is selected, coefficients in consequent part are determined by the least square method. Simulated result illustrates the effectiveness of the proposed technique.

• 한국자동차공학회논문집
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• 제20권3호
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• pp.98-105
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• 2012

Recently, most of the countries started to regulate the emission of vehicle because of the global warming. The engine scooter is also one of the factor which cause the pollution. The hybrid system of a vehicle has many advantages such as fuel saving and emission reduction. The purpose of this study is to choose optimal size of engine, motor and battery for hybrid scooter system using Dynamic programming. The dynamic programming is an effective method to find an optimal solution for the complicated nonlinear system, which contains various constraints of control variables. The power source size of hybrid scooter was chosen through the backward simulator using dynamic programming. From the analysis, we choose the optimal size of each power source. To verify the optimal size of the power source, the Forward simulation was carried out. As a result, the fuel efficiency of hybrid scooter has significantly increased in comparison with that of engine scooter.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1314-1317
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• 1999

In this paper, we design an Adaptive Neuro-Fuzzy Inference System(ANFIS) Precompensator for the performance improvement of conventional proportional integral derivative (PID) controller that the governor system of power plant constantly maintains the load frequency of two-area power system. The ANFIS Precompensator is expressed as the membership functions of premise parameters and the linear combination of consequent parameters by Sugeno's fuzzy if-then rules using nonlinear input-output relation for the set point automatic modification maintaining conventional PID controller. The proposed compensation design technique is hoped to be satisfactory method overcome difficulty of exact modelling and arising problems by the complex nonlinearities of power system, and our design shows merit that is easily implemented by adding an ANFIS precompenastor to an existing PID controller without replacement.

• 제어로봇시스템학회논문지
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• 제13권1호
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• pp.6-14
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• 2007

Modem version of supersonic jet fighter aircraft must have been guaranteed appropriate controllability and stability in HAoA(High Angle of Attack). Limit value of aircraft entering into the departure in HAoA is related to aircraft configuration design. But, the control law such as AoA and yaw-rate limiter is implemented in digital Fly-By-Wire flight control system of supersonic jet fighter to guarantee the aircraft's safety in HAoA. The HAoA flight control law have two parts, one is control law of departure prevention and the other is control law of departure recovery support. The control laws of departure prevention for advanced jet trainer consist AoA limiter, roll command limiter and rudder fader. The control laws of departure recovery support are consist yaw-rate limiter and MPO(Manual Pitch Override) mode. The guideline of pitch rocking using MPO mode is simple, but operating skill of pitch rocking is very difficult by the pilot with inexperience of departure situation. This paper addresses the design and validation of APR(Automatic Pitch Rocker) control law instead of MPO in order to automatic recovery without manual pitch rocking by the pilot. And, recovery characteristic with APR verifies by the nonlinear analysis and pilot evaluation.

• 한국지진공학회논문집
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• 제9권2호통권42호
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• pp.7-15
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• 2005

본 연구에서는 하이브리드 면진장치가 설치된 단자유도 구조물의 동적거동을 예측할 수 있는 수치해석모델을 제안한다. 하이브리드 면진장치는 MR 감쇠기와 마찰진자시스템(FPS)으로 구성된다. MR감쇠기의 동적거동을 모형화하기 위하여 뉴로-퍼지 모델을 사용한다. 다양한 변위, 속도, 전압의 조합을 사용하여 MR 감쇠기의 성능실험을 수행한 후 얻어진 데이터를 이용하여 MR 감쇠기 뉴로-퍼지 모델을 ANFIS로 학습시킨다. FPS의 모형화는 본 연구에서 유도한 비선형 모델식에 근거하여 뉴로-퍼지 모형화방법을 사용하여 이루어진다. 본 연구에서는 MR 감쇠기로 전달되는 제어전압을 조절하기 위하여 퍼지논리제어기를 사용한다. 다양한 지진하중을 사용한 진동대 실험을 통하여 얻은 실험체의 동적응답과와 뉴로-퍼지 모형화방법을 사용한 수치해석의 결과를 비교한다. 뉴로-퍼지 모델을 사용하여 MR 감쇠기와 FPS를 모형화해서 수치해석을 수행한 결과 하이브리드 면진장치의 동적거동을 매우 정확하게 예측할 수 있었다.

• 한국항공우주학회지
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• 제37권5호
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• pp.464-469
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• 2009

본 연구에서는 기존의 초음속 고등훈련기 재형상 모드에 모델추종 적응제어 기법을 적용하여 새로운 개념의 고장허용 제어기를 설계하였다. 실제 비행제어 시스템에 적용할 수 있도록 제어기 설계와 자동 탑재코드 생성에 사용되고 있는 시스템을 이용하여 제어기를 구현하였다. 초음속 고등훈련기의 비실시간 비선형 검증도구로 사용되고 있는 프로그램을 이용하여 시뮬레이션을 수행하여 성능을 검증하였다.

• 제어로봇시스템학회논문지
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• 제8권9호
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• pp.803-811
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• 2002

Machine vision systems are usually used to identify traffic lanes and then determine the steering angle of an autonomous vehicle in real time. The steering angle is calculated using a geometric model of various parameters including the orientation, position, and hardware specification of a camera in the machine vision system. To find the accurate values of the parameters, camera calibration is required. This paper presents a new camera-calibration algorithm using known traffic lane features, line thickness and lane width. The camera parameters considered are divided into two groups: Group I (the camera orientation, the uncertainty image scale factor, and the focal length) and Group II(the camera position). First, six control points are extracted from an image of two traffic lines and then eight nonlinear equations are generated based on the points. The least square method is used to find the estimates for the Group I parameters. Finally, values of the Group II parameters are determined using point correspondences between the image and its corresponding real world. Experimental results prove the feasibility of the proposed algorithm.