Intelligent control and energy optimization in controlled environment agriculture via nonlinear model predictive control of semi-closed greenhouse

Wei-Han Chen, Neil S. Mattson and Fengqi You

Applied Energy, 2022, vol. 320, issue C, No S0306261922006845

Abstract: Greenhouse climate is a highly complex system that contains nonlinearity and dependencies between each system state. This paper proposes a novel nonlinear model predictive control (NMPC) framework for greenhouse climate control to minimize the total control cost mainly coming from energy use. A nonlinear dynamic model of the greenhouse climate, including temperature, humidity, CO2 level, and light intensity, is first constructed based on developed mass balances and energy transport phenomena. Real-world greenhouse climate data and outdoor weather data are gathered to systematically identify the system parameters for the nonlinear greenhouse climate model. The nonlinear dynamic model is then integrated into the proposed NMPC framework which iteratively solves a nonlinear programming problem to obtain the optimal control inputs of fan airflow rate, pad cooling air velocity, heating pipe flow rate, CO2 injection rate, fogging rate, supplemental light intensity, and shade curtain coverage. The stability and feasibility issues of the proposed NMPC framework on a semi-closed greenhouse are explicitly discussed in this work. Case studies on controlling a greenhouse located in Cornell University campus are simulated to demonstrate the performance of the proposed NMPC framework. The results show the NMPC framework could efficiently minimize total control cost and constraint violation. Humidity, CO2 level, and light intensity can be controlled with nearly no violation on the predetermined constraints over different seasons and climate conditions. As for temperature, it is almost always maintained within the acceptable region in winter and spring. On extreme days of summer, there are some temperature violations due to the limited cooling capacity.

Keywords: Controlled environment agriculture; Nonlinear model predictive control; Heating/cooling; CO2 injection; Photosynthetically active radiation (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (11)

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DOI: 10.1016/j.apenergy.2022.119334

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