The precise regulation of temperature and humidity in greenhouses poses a significant control challenge due to the complex, non-linear interactions within the greenhouse climate system, which are further complicated by uncertainties, external influences, and sensor imprecision. This paper introduces a new approach for tackling this challenge, based on the integration of a Kalman filter (KF) and an Extended State Observer (ESO). The ESO is employed for estimating both the unmeasured system variables and the cumulative effect of disturbances. In order to overcome the ESO’s sensitivity to measurement noise, a KF is first implemented for filtering the temperature and humidity variables recorded inside the greenhouse. The interconnection between the KF and the ESO is a coupling which is commonly used in advanced automation systems, such as robotics or drone control. This approach enables control and observation algorithms to adapt in real time to variations in the environment, ensuring a robust performance in the face of uncertainties and disturbances. The estimated state and disturbance variables were then integrated into a robust controller based on state feedback linearization and feedforward disturbance compensation. The simulation results confirm the effectiveness of the proposed control strategy for an accurate greenhouse climate management.
Disturbance compensation, Extended State Observer, Greenhouse, Kalman Filter, Measurement noise, Robust control.
Hatem SLIMENE, Houda MATHLOUTHI, Chemseddine MAATKI, Salim HADJ SAID, Walid HASSEN, Bilel HADRICH, Badr M. ALSHAMMARI, Lioua KOLSI, "A Combined Extended State Observer-Kalman Filter Approach to Robust Greenhouse Climate Control", Studies in Informatics and Control, ISSN 1220-1766, vol. 34(4), pp. 87-98, 2025. https://doi.org/10.24846/v34i4y202508
All articles published by Studies in Informatics and Control (SIC) are published in accordance with the terms and conditions of the Creative Commons Attribution License (CC BY-NC-SA 4.0).