RCGA를 이용한 PID 제어기의 모델기반 동조규칙
DC Field | Value | Language |
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dc.contributor.author | 金到應 | - |
dc.date.accessioned | 2017-02-22T02:26:56Z | - |
dc.date.available | 2017-02-22T02:26:56Z | - |
dc.date.issued | 2003 | - |
dc.date.submitted | 2005-10-19 | - |
dc.identifier.uri | http://kmou.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002173764 | ko_KR |
dc.identifier.uri | http://repository.kmou.ac.kr/handle/2014.oak/8424 | - |
dc.description.abstract | Over 60 years, the proportional-integral-derivative(PID) controller has been especially popular in industrial processes, such as chemical, petroleum, power and manufacturing industries due to its simple structure and robustness. Since the performance of the PID controller depends highly on its three parameters, the proper tuning of the parameters is required to guarantee acceptable control performance. Therefore, a number of tuning methods, such as the Ziegler-Nichols methods, the Cohen-Coon method, and the IMC method have been proposed. These conventional tuning methods are based on experience and experiment. In this thesis, a method for obtaining model-based tuning rules for the PID controller are proposed incorporating with real-coded genetic algorithms. First, the optimal parameter sets for step set-point tracking are obtained based on the first-order time delay model and a real-coded genetic algorithm as an optimization tool. As for assessing the performance of the controller, performance indices(IAE, ISE and ITAE) are adopted. Then, tuning rules are derived using the tuned parameter sets, potential rule models and another real-coded genetic algorithm. A set of simulation works are carried out to verify the effectiveness of the proposed rules. | - |
dc.description.tableofcontents | 목차 Abstract = iii 제 1 장 서론 = 1 제 2 장 PID 제어기와 동조규칙 = 3 2.1 PID 제어기 = 3 2.2 기존의 동조규칙 = 5 2.2.1 Ziegler-Nichols(Z-N) 동조법 = 5 2.2.2 Cohen-Coon(C-C) 동조법 = 9 2.2.3 IMC 동조법 = 10 2.2.4 Lopez ITAE(L-ITAE) 동조법 = 11 제 3 장 RCGA를 이용한 최적 동조규칙 = 13 3.1 PID 제어시스템의 무차원화 = 13 3.1.1 제어기 및 제어대상 = 13 3.1.2 제어기 및 제어대상의 무차원화 = 14 3.2 유전알고리즘을 이용한 최적동조 = 16 3.2.1 최적화 도구로서의 RCGA = 16 3.2.2 성능지수 = 17 3.2.3 최적 PID 계수집합 = 19 3.3 제안한 동조규칙 = 22 제 4 장 시뮬레이션 및 결과검토 = 26 4.1 예제 1 = 26 4.1.1 모델의 근사화 = 26 4.1.2 PI 제어기의 응답비교 = 29 4.1.3 PID 제어기의 응답비교 = 32 4.2 예제 2 = 34 4.2.1 모델의 근사화 = 34 4.2.2 PI 제어기의 응답비교 = 36 4.2.3 PID 제어기의 응답비교 = 39 4.3 예제 3 = 41 4.3.1 모델의 근사화 = 41 4.3.2 PI 제어기의 응답비교 = 43 4.3.3 PID 제어기의 응답비교 = 46 제 5 장 결론 = 48 참고문헌 = 49 | - |
dc.publisher | 韓國海洋大學校 | - |
dc.title | RCGA를 이용한 PID 제어기의 모델기반 동조규칙 | - |
dc.title.alternative | Model-based Tuning Rules of the PID Controller Using Real-coded Genetic Algorithms | - |
dc.type | Thesis | - |
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