• 제어로봇시스템학회논문지
• /
• 제10권10호
• /
• pp.855-868
• /
• 2004

There are several types of singularities in controlling robotic manipulators: kinematic singularity, algorithmic singularity, semi-kinematic singularity, semi-algorithmic singularity, and representation singularity. The kinematic and algorithmic singularities have been investigated intensively because they are not predictable or difficult to avoid. The problem with these singularities is an unnecessary performance reduction in non-singular region and the difficulty in performance tuning. Tn this paper, we propose a method of avoiding kinematic and algorithmic singularities by applying a task reconstruction approach while maximizing the task performance by calculating singularity measures. The proposed method is implemented by removing the component approaching the singularity calculated by using singularity measure in real time. The outstanding feature of the proposed task reconstruction method (TR-method) is that it is based on a local task reconstruction as opposed to the local joint reconstruction of many other approaches. And, this method has dynamic task priority assignment feature which ensures the system stability under singular regions owing to the change of task priority. The TR-method enables us to increase the task controller gain to improve the task performance whereas this increase can destabilize the system for the conventional algorithms in real experiments. In addition, the physical meaning of tuning parameters is very straightforward. Hence, we can maximize task performance even near the singular region while simultaneously obtaining the singularity-free motion. The advantage of the proposed method is experimentally tested by using the 7-dof spatial manipulator, and the result shows that the new method improves the performance several times over the existing algorithms.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.2102-2107
• /
• 2005

In this paper, a real-time optimization method for nonlinear dynamical systems is proposed. The proposed method is based on the algorithms of numerical solutions for optimal control problems. We deal with a real-time collision-free motion control of a nonholonomic mobile robot, which has input restrictions of actuators. The effectiveness of the algorithmic method is demonstrated through numerical and experimental results. The mobile robot which we have developed is able to avoid moving obstacles skillfully. Therefore the proposed controller works well in real time.

• 정보처리학회논문지A
• /
• 제11A권1호
• /
• pp.97-108
• /
• 2004

본 논문은 자바 프로그램에서 논리적인 오류를 발견하기 위해 알고리즈믹 디버깅 기술의 이용을 제안한다. 알고리즈믹 디버깅 기술은 원시프로그램으로부터 실행 트리를 생성하고, 실행 트리로부터 프로그램 내에 포함된 논리적인 오류를 하향식 방법으로 발견하는 반자동화 디버깅기술이다. 따라서 알고리즈믹 디버깅 기술은 다양한 프로그래밍 언어에 알맞은 실행 트리를 생성하는 것이 중요하다. 주 논문에서는 자바 프로그램으로부터 실행 트리를 생성하는 방법을 제안하고 예제론 통해서 자바 프로그램을 위한 알고리즈믹 디버깅 기술을 확인한다. 이 접근은 전통적인 순차적 디버깅 기술보다 사용자와 디버깅 시스템 사이에서 상호작용의 수를 줄일 수 있다.

• 전력전자학회논문지
• /
• 제7권1호
• /
• pp.11-17
• /
• 2002

디지털 회로 설계 방법의 하나인 Algorithmic State Machine (ASM)을 이용하여 반복운동을 하는 모터의 위치를 오차 없이 검출할 수 있는 방법에 대한 연구를 수행하였다. 이를 위하여 모터의 운동방향 변화 시 증분형 엔코더의 출력 패턴을 분석하고 이를 바탕으로 상태도 및 상태 테이블을 구성하였으며 모터의 운동방향 변화 시 정확하게 변화시점을 검출할 수 있는 디지털 회로를 설계하였다 설계된 회로의 유용성을 검증하기 위하여 시뮬레이션 및 실험을 수행하였다. 시뮬레이션 결과 모터의 운동 방향이 변화하는 모든 경우에 대해서 제안된 회로를 이용하면 오차 없이 모터의 위치를 검출할 수 있음을 입증하였다.

• 한국펄프종이공학회:학술대회논문집
• /
• 한국펄프종이공학회 2004년도 춘계학술발표논문집
• /
• pp.107-114
• /
• 2004

In this work the Model algorithmic control method is applied to control the grade change operations in paper mills. The neural network model for the grade change operations is identified first model is then extracted from the neural model. Results of simulations for MAC control of grade change operations are compared with plant operation data response. From the comparison, we can see that the proposed MAC method exhibits faster response for the grade change of paper and achieves stable steady-state.

• 대한산업공학회지
• /
• 제38권3호
• /
• pp.198-207
• /
• 2012

In product or process parameter design, the case of multiple performance characteristics appears more commonly than that of a single characteristic. Numerous methods have been developed to deal with such multi-characteristic parameter design (MCPD) problems. Among these, this paper considers three representative methods, which are respectively based on the desirability function (DF), grey relational analysis (GRA), and principal component analysis (PCA). These three methods are then used to solve the MCPD problems in ten case studies reported in the literature. The performance of each method is evaluated for various combinations of its algorithmic parameters and alternatives. Relative performances of the three methods are then compared in terms of the significance of a design parameter and the overall performance value corresponding to the compromise optimal design condition identified by each method. Although no method is significantly inferior to others for the data sets considered, the GRA-based and PCA-based methods perform slightly better than the DF-based method. Besides, for the PCA-based method, the compromise optimal design condition depends much on which alternative is adopted while, for the GRA-based method, it is almost independent of the algorithmic parameter, and therefore, the difficulty involved in selecting an appropriate algorithmic parameter value can be alleviated.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.73-77
• /
• 2003

This paper presents a high-speed algorithmic analog-to-digital converter (ADC), which is based on gray coding. The realization method makes use of a two-input maximum circuit to provide a high-speed operation and a low-distortion in the transfer characteristic. The proposed ADC based on the CMOS integrated circuit technique is simple and suitable for implementing a highresolution ADC. The performances of the proposed circuit were studied using the PSPICE analog simulation program. The simulation-results verifying the circuit performances are agreed with the expected values.

• 한국정보디스플레이학회:학술대회논문집
• /
• 한국정보디스플레이학회 2005년도 International Meeting on Information Displayvol.II
• /
• pp.1171-1174
• /
• 2005

This thesis provides a new digital convergence method and apparatus which uses area photo sensor and new analog to digital algorithmic to identify the correct digital pattern position factor of the projection system. This method and apparatus can be applied to the convergence correction in a TV receiver with a display that comprises a display screen with photo sensors positioned adjacent to screen edges. It also can be applied to the manufacture process detection of the projection system to adjust the associative convergence parameter. In this paper, demonstrate how this convergence detecting algorithmic was implemented with four area photo sensors of special designed pattern to the rear projection CRT TV.

• 펄프종이기술
• /
• 제36권5호
• /
• pp.11-20
• /
• 2004

In this work the Model Algorithmic Control (MAC) method is applied to control the grade change operations in paper mills. The neural network model for the grade change operations is identified first and the impulse model is extracted from the neural network model. Results of simulations for MAC control of grade change operations are compared with plant operation data. The major contribution of the present work is the application of MAC in the industrial plants based on the identification of neural network models. We can confirm that the proposed MAC method exhibits faster responses and less oscillatory behavior compared to the plant operation data in the grade change operations.

• 한국지능시스템학회논문지
• /
• 제7권2호
• /
• pp.3-15
• /
• 1997

퍼지논리를 적용하기 위해서는 두가지 과제가 이루어져야 하는데 그것은 퍼지룰의 유도와 맴버쉽함수의 결정이다. 이 과제는 어렵고 또한 시간을 요하게 된다. 본 논문에서는 문제에 적용 가능한 멤버쉽함수와 퍼지룰을 자동으로 유도하기 위한 알고리즘적 방법을 제시하고 있다. 이 알고리즘적 방법은 샘플을 구분하는 엔트로피 최소화의 원리에 입각하고 있다. 멤버쉽함수는 샘플을 연속적으로 구분하여 이루어지며 퍼지룰 또한 엔트로피 최소화 원리에 의하여 이루어진다. 퍼지룰의 유도에서는 룰 비중 또한 같이 계산된다. 결정 문제에 적용을 위한 추론법 및 방법도 논의되었다.