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Sensors 2012, 12(5), 5328-5348; doi:10.3390/s120505328
Article

Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network

1
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1,2,* , 2,*  and 1
Received: 21 January 2012 / Revised: 18 March 2012 / Accepted: 19 April 2012 / Published: 26 April 2012
(This article belongs to the Section Physical Sensors)
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Abstract

This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production.
Keywords: nonlinear adaptive control; neuro-PID control; Radial Basis Function (RBF); greenhouse environment control; Genetic Algorithm (GA) nonlinear adaptive control; neuro-PID control; Radial Basis Function (RBF); greenhouse environment control; Genetic Algorithm (GA)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Zeng, S.; Hu, H.; Xu, L.; Li, G. Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network. Sensors 2012, 12, 5328-5348.

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