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Optimization of Generalized Predictive Control (GPC) Tuning Parameters By Response Surface Methodology (RSM)

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJCA) 바로가기
  • 간행물
    International Journal of Control and Automation SCOPUS 바로가기
  • 통권
    Vol.8 No.2 (2015.02)바로가기
  • 페이지
    pp.393-408
  • 저자
    Adnan Aldemir, Hale Hapoğlu, Mustafa Alpbaz
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A241855

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원문정보

초록

영어
Response Surface Methodology(RSM) was successfully applied to a process simulator for optimization of Generalized Predictive Control(GPC) tuning parameters. Wireless experimental input/output data obtained from process simulator. GPC algorithm which is written in MATLAB is utilized to wireless temperature control experiments achieved by using MATLAB/Simulink program.The efficiency of the GPC is observed by calculating the integral of the square of the error (ISE) and the integral of the absolute value of the error (IAE) from experimental results which was optimized by the application of RSM. The three independent variables, which had been found the most effective variables on the GPC by screening experiments, were determined as NU, N2 and λ as minimum prediction horizon, maximum prediction horizon and control weighting, respectively. The quadratic models were developed through RSM in terms of related independent variables to describe the ISE and IAE as the two response. Based on statistic analysis, optimum GPC tuning parameters of NU (X1), N2 (X2) and λ (X3) for minimize the ISE were determined to be 1.7922, 1.9453 and 0.0642 and for minimize the IAE were determined to be 1.8880, 1.9752 and 0.0612, respectively. Calculated optimum points of GPC tuning parameters are close to based on ISE and IAE results. The data evaluated from the quadratic model were good agreement with those measured experimentally. The wireless temperature control is successfully applied to the process simulator and wireless control technique is proposed for various application areas.

목차

Abstract
 1. Introduction
 2. Generalized Predictive Control (GPC) Technique
 3. Experimental System Description and Methods
  3.1 Experimental Design and Analysis
 4. Results and Discussion
  4.1 Analysis of Variance (ANOVA) for ISE and IAE
 5. Conclusions
 Acknowledgements
 References

키워드

GPC RSM ISE IAE wireless process control MATLAB/Simulink optimization

저자

  • Adnan Aldemir [ Ankara University, Faculty of Engineering, Department of Chemical Engineering, 06100, Ankara, Turkey ]
  • Hale Hapoğlu [ Ankara University, Faculty of Engineering, Department of Chemical Engineering, 06100, Ankara, Turkey ]
  • Mustafa Alpbaz [ Ankara University, Faculty of Engineering, Department of Chemical Engineering, 06100, Ankara, Turkey ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJCA) [Science & Engineering Research Support Center, Republic of Korea(IJCA)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Control and Automation
  • 간기
    월간
  • pISSN
    2005-4297
  • 수록기간
    2008~2016
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Control and Automation Vol.8 No.2

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