Nonlinear adaptive Neuro-PID controller design for greenhouse environment based on RBF network

This paper presents a hybrid control strategy, combining RBF network with the conventional PID controller, for the greenhouse climate control. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. The results show that the proposed strategy has good adaptability, strong robustness while achieving satisfactory control performance for the complex and nonlinear time-varying greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production.

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