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A Multi-Modelling Approach and Optimal Control of Greenhouse Climate

  • Ayoub MoufidEmail author
  • Najib Bennis
Conference paper
Part of the Advances in Science, Technology & Innovation book series (ASTI)

Abstract

The objective of greenhouse climate control is to improve the cultural development and to minimize the production costs. In this paper, we propose a comparison between two approaches to modelling and control greenhouse’s inside climate. This one is defined by internal temperature and hygrometry. The classical approach is based on a single linear model to describe the dynamic of greenhouse internal climate and using a strategy control to regulate the microclimate inside the greenhouse. The multi-modelling approach aims to reduce the complexity of the system in terms of variables to take into account in modelling and controllers design. Therefore, we have developed two linear models for representing the greenhouse inside climate in two different durations. Those diurnal and nocturnal phases. For the control of greenhouse inside climate based on finite-horizon optimal control, we present two methods. The first one is a classical method and consists of controlling the internal climate by using a single controller for all days. The other one is based on two models and two controllers for nocturnal and diurnal phases. For the needs of simulation purpose, we have used a nonlinear model to describe more effectively the behaviour of greenhouse dynamic climate. A successful feasibility study of the proposed controller is presented and simulation results show good performances despite the high interaction between the process internal and external variables. The comparison results confirm the superiority of a multi-modelling approach.

Keywords

Greenhouse Climate control Multi-modelling Diurnal and nocturnal phases Identification Finite-horizon optimal control 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.ENSET of RabatUniversity Mohamed V of RabatRabatMorocco

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