Receding horizon based greenhouse air temperature control using grey Wolf optimization algorithm

Rahul Singhal; Rajesh Kumar

doi:10.1109/UPCON.2016.7894620

Receding horizon based greenhouse air temperature control using grey Wolf optimization algorithm

Rahul Singhal, Rajesh Kumar

Malaviya National Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

Abstract

This work describes the receding horizon control of an inside air temperature of greenhouse using the grey wolf optimization algorithms based on constraints on manipulative variables. Its performance being compared with that of Genetic algorithm and Particle swarm optimization. Classical control methods are difficult to implement for greenhouse air temperature control problem because of high nonlinear and complex nature of system. Meta-heuristic based algorithms are implemented because of their easy to understand, appropriate for different types of problems, stochastic nature helps in evading local extrema and derivative dependency. The results of GWO clearly shown better power saving & smoother control when compared with already implemented GA & PSO meta-heuristic algorithms for greenhouse air temperature control.

Original language	English
Title of host publication	2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	32-37
Number of pages	6
ISBN (Electronic)	9781509053841
DOIs	https://doi.org/10.1109/UPCON.2016.7894620
Publication status	Published - 7 Apr 2017
Externally published	Yes
Event	2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016 - Varanasi, India Duration: 9 Dec 2016 → 11 Dec 2016

Publication series

Name	2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016

Conference

Conference	2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016
Country/Territory	India
City	Varanasi
Period	9/12/16 → 11/12/16

Keywords

Genetic algorithm (GA)
Greenhouse temperature control
Grey Wolf Optimization (GWO)
Particle Swarm Optimization (PSO)
Receding Horizon Control (RHC)

ASJC Scopus subject areas

Hardware and Architecture
Energy Engineering and Power Technology
Electrical and Electronic Engineering

Access to Document

10.1109/UPCON.2016.7894620

Cite this

Singhal, R., & Kumar, R. (2017). Receding horizon based greenhouse air temperature control using grey Wolf optimization algorithm. In 2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016 (pp. 32-37). Article 7894620 (2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UPCON.2016.7894620

Singhal, Rahul ; Kumar, Rajesh. / Receding horizon based greenhouse air temperature control using grey Wolf optimization algorithm. 2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 32-37 (2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016).

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title = "Receding horizon based greenhouse air temperature control using grey Wolf optimization algorithm",

abstract = "This work describes the receding horizon control of an inside air temperature of greenhouse using the grey wolf optimization algorithms based on constraints on manipulative variables. Its performance being compared with that of Genetic algorithm and Particle swarm optimization. Classical control methods are difficult to implement for greenhouse air temperature control problem because of high nonlinear and complex nature of system. Meta-heuristic based algorithms are implemented because of their easy to understand, appropriate for different types of problems, stochastic nature helps in evading local extrema and derivative dependency. The results of GWO clearly shown better power saving & smoother control when compared with already implemented GA & PSO meta-heuristic algorithms for greenhouse air temperature control.",

keywords = "Genetic algorithm (GA), Greenhouse temperature control, Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Receding Horizon Control (RHC)",

author = "Rahul Singhal and Rajesh Kumar",

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language = "English",

series = "2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016",

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Singhal, R & Kumar, R 2017, Receding horizon based greenhouse air temperature control using grey Wolf optimization algorithm. in 2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016., 7894620, 2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016, Institute of Electrical and Electronics Engineers Inc., pp. 32-37, 2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016, Varanasi, India, 9/12/16. https://doi.org/10.1109/UPCON.2016.7894620

Receding horizon based greenhouse air temperature control using grey Wolf optimization algorithm. / Singhal, Rahul; Kumar, Rajesh.
2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 32-37 7894620 (2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - This work describes the receding horizon control of an inside air temperature of greenhouse using the grey wolf optimization algorithms based on constraints on manipulative variables. Its performance being compared with that of Genetic algorithm and Particle swarm optimization. Classical control methods are difficult to implement for greenhouse air temperature control problem because of high nonlinear and complex nature of system. Meta-heuristic based algorithms are implemented because of their easy to understand, appropriate for different types of problems, stochastic nature helps in evading local extrema and derivative dependency. The results of GWO clearly shown better power saving & smoother control when compared with already implemented GA & PSO meta-heuristic algorithms for greenhouse air temperature control.

AB - This work describes the receding horizon control of an inside air temperature of greenhouse using the grey wolf optimization algorithms based on constraints on manipulative variables. Its performance being compared with that of Genetic algorithm and Particle swarm optimization. Classical control methods are difficult to implement for greenhouse air temperature control problem because of high nonlinear and complex nature of system. Meta-heuristic based algorithms are implemented because of their easy to understand, appropriate for different types of problems, stochastic nature helps in evading local extrema and derivative dependency. The results of GWO clearly shown better power saving & smoother control when compared with already implemented GA & PSO meta-heuristic algorithms for greenhouse air temperature control.

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KW - Particle Swarm Optimization (PSO)

KW - Receding Horizon Control (RHC)

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Singhal R, Kumar R. Receding horizon based greenhouse air temperature control using grey Wolf optimization algorithm. In 2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 32-37. 7894620. (2016 IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering, UPCON 2016). doi: 10.1109/UPCON.2016.7894620

Receding horizon based greenhouse air temperature control using grey Wolf optimization algorithm

Abstract

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Keywords

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