A Neuro-Dynamic Programming-Based Optimal Controller for Tomato Seedling Growth in Greenhouse Systems

• Published in: Neural processing letters Vol. 24; no. 3; pp. 241 - 260
• Main Authors: Pucheta, J., Patiño, H., Fullana, R., Schugurensky, C., Kuchen, B.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer 01.12.2006; Springer Nature B.V
• Subjects: Actuators; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Connectionism. Neural networks; Controllers; Cost function; Dynamic programming; Dynamical systems; Exact sciences and technology; Greenhouses; Microclimate; Nonlinear dynamics; Process variables; Tomatoes; Process planning; Minimization; Climate models; Neural network; neuro-dynamic programming; Neurocontrollers; Design process; Optimal control; Agriculture; intelligent agriculture; Dynamic programming; greenhouse control systems; Actuator; State constraint; Mathematical programming

This work proposes a neuro-dynamic programming-based optimal controller to guide the growth of tomato seedling crops by manipulating its environmental conditions in a greenhouse. The neurocontroller manages the growth development of the crop, while minimizing a predefined cost function that consider...