Comparison between Two Adaptive Controllers Applied to Greenhouse Climate Monitoring

Abstract

Abstract-This paper presents a study of a multivariable Adaptive Generalized Predictive Controller and its application to control the thermal behaviour of an agricultural greenhouse, which is composed of a number of different elements (cover, internal air, plants, soil, actuators and sensors). The thermal model was obtained after the study of energy balances reacting the physical behavior of the greenhouse. For this reason, we opted to estimate the dynamic model of the greenhouse with algorithm based on recursive least squares (RLS) method. Simulation results are exposed to show the controller's performances in terms of response time, stability and the rejection of disturbances.

Intelligent control for an experimental greenhouse climate based on ANFIS Technology

“…To deal with market globalization, such strategies should not only lead to good efficiency but also to reduce production cost. Some years ago, diverse control techniques were proposed like adaptive control [4]- [5], optimal control [6], robust control [7], predictive control [8]- [9] and sliding mode control [10] … As stated before, greenhouse system presents significant non-linear behaviors. The techniques of artificial intelligence (AI) are recognized as a powerful tool to solve non-linear issues.…”