• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1343-1346
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• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.302-307
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• 2001

This research is concerned with the development of a real-time adaptive PPF controller for the active vibration suppression of smart structure. In general, the tuning of the PPF controller is carried out off-line. In this research, the real-time learning algorithm is developed to find the optimal filter frequency of the PPF controller in real time and the efficacy of the algorithm is proved by implementing it in real time. To this end, the adaptive algorithm is developed by applying the gradient descent method to the predefined performance index, which is similar to the method used popularly in the optimization and neural network controller design. The experiment was carried out to verify the validity of the adaptive PPF controller developed in this research. The experimental results showed that adaptive PPF controller is effective for active vibration control of the structure which is excited by either impact or harmonic disturbance. The filter frequency of the PPF controller can be tuned in a very short period of time thus proving the efficiency of the adaptive PPF controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.990-995
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• 1990

A minimum-time trajectory planning for two robot arms with designated paths and coordination is proposed. The problem considered in this paper is a subproblem of hierarchically decomposed trajectory planning approach for multiple robots : i) path planning, ii) coordination planning, iii) velocity planning. In coordination planning stage, coordination space, a specific form of configuration space, is constructed to determine collision region and collision-free region, and a collision-free coordination curve (CFCC) passing collision-free region is selected. In velocity planning stage, normal dynamic equations of the robots, described by joint angles, velocities and accelerations, are converted into simpler forms which are described by traveling distance along collision-free coordination curve. By utilizing maximum allowable torques and joint velocity limits, admissible range of velocity and acceleration along CFCC is derived, and a minimum-time velocity planning is calculated in phase plane. Also the planning algorithm itself is converted to simple numerical iterative calculation form based on the concept of neural optimization network, which gives a feasible approximate solution to this planning problem. To show the usefulness of proposed method, an example of trajectory planning for 2 SCARA type robots in common workspace is illustrated.

• 센서학회지
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• 제14권6호
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• pp.409-414
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• 2005

For an intelligent vehicle driving which uses magnetic markers and magnetic sensors, we can get every kind of road information while moving the vehicle if we use the code that is encoded with N, S pole direction of markers. If we make it an only aim to move the vehicle, it becomes easy to control the vehicle the more we put markers close. By the way, to recognize the direction of a marker pole it is much better that the markers have no effect each other. To get road informations and move the vehicle autonomously we propose the methods of arranging magnetic sensors and algorithm of recognizing the position of the vehicle with those sensors. We verified the effectiveness of the methods with computer simulation.

• 정보처리학회논문지B
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• 제12B권3호
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• pp.257-264
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• 2005

사회가 발전하면서 자동차의 수요도 세계적으로 급증하고 있다. 교통제어나 차량에 연관된 범죄 둥을 해결하는데 자동차의 인식 기술이 중요하기 때문에 이에 관련된 번호판 인식이나 교통량 측정에 관한 연구는 오래 전부터 수행되어왔다. 본 논문에서는 주행차량의 제조회사와 차량 모델을 인식하는 방법을 제시하였다. 차종의 인식은 차량 전면부 영역의 질감을 이용하여 인식하였다. 번호판 상단의 라디에이터 영역에서 질감 특징자를 추출하여 신경망을 통한 차종별 학습을 시켜서 인식을 시도하였다. 제안 알고리즘에서 차종의 정인식은 $93.7\%$, 이종차량의 감별은 $99.7\%$로 양호하게 나타났다.

• 융합신호처리학회논문지
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• 제5권1호
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• pp.32-39
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• 2004

생체 뉴론은 일반적으로 지속적 또는 과도적인 카오틱 특성을 가지고 있다. 생체 뉴론의 카오틱 반응에 대한 분석적인 해석은 아직까지 이루어지지 않고 있다. 동적 카오틱 반응에 대한 카오틱 뉴런의 과도 카오틱 특성은 지역 수렴 문제를 극복하는데 도움이 되지만 일반적으로 지속적인 카오틱 응답은 최적화 문제에 악영향을 미치게 되므로 초기 카오틱 특성은 사라져야 한다. 패턴 인식, 확인, 예측, 그리고 제어에 사용되는 대부분의 신경회로망 응용에 있어서 필요한 최적화 문제를 해결하기 위해서는 뉴론은 한 개의 안정적인 고정점을 가지고 있어야 한다. 본 논문에서는 동적 카오틱 뉴런의 동적 특성과 카오틱 응답을 발생시키는 조건을 분석하고, 카오틱 뉴런의 수렴조건을 제안하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.47-50
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• 2000

In this paper, an optimal identification method using Multi-FNN(Fuzzy-Neural Network) is proposed for model ins of nonlinear complex system. In order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM clustering algorithm which carry out the input-output data preprocessing function and Genetic Algorithm which carry out optimization of model. The proposed Multi-FNN is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. HCM clustering method which carry out the data preprocessing function for system modeling, is utilized to determine the structure of Multi-FNN by means of the divisions of input-output space. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model, To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• 한국지능시스템학회논문지
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• 제12권1호
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• pp.61-66
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• 2002

본 논문에서는 Flexible Manipulator의 제어를 위해 퍼지제어의 제약인 멤버쉽 함수, 퍼지규clr을 유전알고리즘으로 조정, 최적화 하는 새로운 제어기를 설계하였다. 사용된 유전알고리즘은 Steady State Genetic 알고리즘과 Adaptive 유전 알고리즘의 합성이다. 제안한 제어기는 Flexible Manipulator의 끝점 무게 0.8kmg, 최대속도 1m/s의 경우, 퍼지제어에 비해 오차가 90.8% 감소하고 신경회로망을 이용한 퍼지제어에 비하여는 31.8% 감소하였으며 진화전략과 퍼지제어합성에 의한 제어기보다는 오차가 31.3% 감소하는 통 제어성능과 그 유용성이 우수함을 확인하였다.

• 대한전기학회논문지:전력기술부문A
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• 제52권8호
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• pp.471-480
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• 2003

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. Among the reasons for its complexity are the system size, conflicting requirements of estimator accuracy, reliability in the presence of transducer noise and data communication failures, adaptability to change in the network topology and cost minimization. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs) which is widely used in areas such as: optimization of the objective function, learning of neural networks, tuning of fuzzy membership functions, machine learning, system identification and control. This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2569-2571
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• 2000

In the vehicle steering system, we can consider two methods to steer the vehicle. One is a front wheel steering(FWS), the other is a four wheel steering(4WS). The four wheel steering method has been recently introduced to improve the steering performance. In this paper, we present a design of the four wheel steering controller. First, we constructed the neural network two degree of freedom PID controller to control the 4WS system. Then we compared the performance of conventional PID controller with our proposed controller in terms of yaw rate and side slip velocity. The computer simulation results show that 4WS system controlled by the proposed controller has well driving performances than the other.