메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술대회자료
저자정보
Zhang Qihang (Shanghai Marine Diesel Engine Research Institute) Sun Jianfeng Shi Xingchen (Shanghai Marine Diesel Engine Research Institute) Yang Weidong
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2024
발행연도
2024.10
수록면
23 - 28 (6page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
In this paper, taking the four-stroke medium-speed diesel engine of China's own brand as the controlled object, a deep reinforcement learning-based control parameter self-tuning control algorithm is designed for the speed control problem of marine diesel engine in steady state and transient working conditions. The results show that when the speed of the ship medium-speed diesel engine is destabilised due to the extreme initialisation parameters of the PI controller in the steady state process, the speed control algorithm based on the PI self-tuning of DQN can make the
speed stabilise as soon as possible; and the speed control algorithm can make the speed fluctuation reduce significantly and reduce the time for the system to stabilise in the transient process. In the transient process, when the PI controller control parameters change suddenly and lead to abnormal speed, the speed control algorithm can fine-tune the control parameters so that the speed deviation can be reduced as soon as possible.

목차

Abstract
Ⅰ. INTRODUCTION
Ⅱ. ENGINE MODELLING
Ⅲ. THEORY OF SPEED CONTROL ALGORITHMS FOR MARINE DIESEL ENGINE
Ⅳ. DESIGN AND SIMULATION OF SPEED CONTROL ALGORITHM FOR MARINE DIESEL ENGINE
Ⅴ. CONCLUSION
REFERENCES

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

최근 본 자료

전체보기

댓글(0)

0