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DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2017.11
- 수록면
- 786 - 789 (4page)
이용수
초록· 키워드
Control performance is significantly affected by two control parameters, sampling frequency and sensing to actuating delay. Higher sampling frequency and shorter delay makes better control performance, however, it makes the system difficult to schedule in a multitasking environment, where multiple control tasks share CPU resource. To maintain high frequency and short delay, task periods and deadlines should be kept very short that eventually leads to system unschedulability. Making the problem more complex, in AUTOSAR-based vehicle control systems, a large number of small functions runnables are mapped to periodic tasks that matches each runnable’s own period and data flow between sensing and actuation goes through a sequence of runnables with different periods. With this motivation, we present a novel algorithm that determines runnable periods that provides both the optimal control performance and system schdulability for AUTOSAR. Assuming that control performance is given as a linear function of frequency and delay, we use Lagrange multiplier to find the set of optimal periods with a constraint that the system utilization is less than 100% with EDF scheduling algorithm.
#AUTOSAR(오토사)
#Runnable(러너블)
#Control Performance(제어성능)
#DAG(비 순환 방향 그래프)
#Delay(지연시간)
#Lagrange Multiplier(라그랑주 승수법)
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목차
- Abstract
- 1. 서론
- 2. 시스템 모델링
- 3. 실험 환경 및 결과
- 4. 결론
- References
참고문헌
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