지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2013.5
- 수록면
- 51 - 54 (4page)
이용수
초록· 키워드
오류제보하기
In general, industrial robots carry out repetitive tasks on production lines. Although robot control technology has really improved, tracking error still occurs when a robot performs repetitive tasks under the influence of iterative noise and other disturbances. To solve these problems, Iterative Learning Control (ILC) was proposed. ILC is a learning control that can reduce the error of the current motion by using the error of the previous run. ILC using Linear Matrix Inequality (LMI), the one of ILC algorithms, can be applied to designing a simple controller in the frequency domain of complex systems. In this paper, learning function (L-function) of ILC is designed by using an LMI algorithm and control performance was compared for different various orders of L-function. Also, Q-filter is designed based on the dynamics of the designed system. To confirm the improved performance of the algorithms, designed ILC controller is applied to a 2-link planer robot manipulator in simulations.
목차
Abstract
1. 서론
2. 반복학습제어
3. 시뮬레이션
4. 결론
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UCI(KEPA) : I410-ECN-0101-2014-560-002949415