Kalman filtering on greenhouse climate control

This study is on the development of an extended Kalman filter used in conjunction with a nonlinear feedback controller for greenhouse climate control systems. In this paper, the measured variables are corrupted by the sensor noises and the system dynamics is influenced by process noises as well. So an extended Kalman filter algorithm has been carried out to estimate the states and to filter out the noises in parallel to augment the proposed control design. The proposed method not only decreases the errors between the current states and their desired values, but also smoothes the control signals, which will increase the life time of the actuators and decrease the operating cost and low investment capacity of growers. The simulation results verify the effectiveness of the proposed approach and suggest it as a promising way for greenhouse climate control.

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