Multi-objective tuning of nonlinear PID controllers for greenhouse environment using Evolutionary Algorithms

This paper investigates the issue of PID-controller parameters tuning for a greenhouse climate control system using Evolutionary Algorithms based on multiple performance measures such as good set-point tracking and smooth control signals. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is validated for greenhouse climate control by minimizing the integrated time square error (ITSE) and the control increment or rate in a series of simulations. The results show that the controllers by tuning the gain parameters can achieve good control performance through step responses such as small overshoot, fast settling time, and less rise time and steady state error. Maybe it is quite an effective and promising tuning method using multi-objective algorithms in the complex greenhouse production.