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NSGA-II-based nonlinear PID controller tuning of greenhouse climate for reducing costs and improving performances

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Abstract

The traditional tuning scheme of proportional, integral, and derivative (PID) controller parameters usually lay more emphasis on control performances than economic profits. As a result, the corresponding control performance is improved, but such case may lead to high production costs. In this paper, a new tuning methodology for multiple PID controllers from an economic point of view by incorporating multiple performance measures and production costs based on nondominated sorting genetic algorithm-II (NSGA-II) is presented. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is tested through step responses for greenhouse climate control by minimizing the indices of overall performance and production cost in a simulation experiment. The results show that the controllers by tuning the gain parameters can achieve good control performance at a relatively low cost. Maybe it is a quite effective and promising tuning method by using this method in the complex greenhouse production.

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Acknowledgments

The authors would like to express their appreciation to the referees for their helpful comments and suggestions. This work was supported by the key task of high-tech in 863 project for the 12th five-year plan (Grant No. 2012AA10A507), the National Natural Science Foundations of China (Grant No. 61174090, 61174023, 60903144, and 61272313). And supported by Natural Science Foundation (Grant No. Y1110880), Science and Technology Planning Project (Grant No. 2012C21015) and Forestry Department (Grant No. 2010B13) of Zhejiang Province of China, and also supported by BEACON (An NSF Science and Technology Center for the Study of Evolution in Action, Coop. Agmt.) of USA under the Grant No. DBI-0939454.

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Authors and Affiliations

  1. School of Information Engineering, Zhejiang Agriculture and Forestry University, Lin’an City, 311300, Zhejiang Province, China

    Haigen Hu & Songwei Zeng

  2. Department of Control Science and Engineering, Tongji University, Shanghai, 200092, China

    Lihong Xu

  3. Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, 48824, USA

    Erik D. Goodman

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  1. Haigen Hu
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  2. Lihong Xu
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  3. Erik D. Goodman
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  4. Songwei Zeng
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Correspondence to Lihong Xu.

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Hu, H., Xu, L., Goodman, E.D. et al. NSGA-II-based nonlinear PID controller tuning of greenhouse climate for reducing costs and improving performances. Neural Comput & Applic 24, 927–936 (2014). https://doi.org/10.1007/s00521-012-1312-8

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  • DOI: https://doi.org/10.1007/s00521-012-1312-8

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