Abstract: Proportional integral plus feedforward (PI+FF) control was proposed for identifying the pipe temperature in hot water heating greenhouse. To get satisfying control result, ten coefficients must be adjusted properly. The data for training and testing the radial basic function (RBF) neural-networks model of greenhouse were collected in a 1028 m² multi-span glasshouse. Based on this model, a method of coefficients adjustment is described in this article.

Key words: PI control, Greenhouse, Temperature, Neural networks

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