A discussion of challenges related to the modeling and control of
greenhouse crop growth, this book presents state-of-the-art answers to
those challenges. The authors model the subsystems involved in
successful greenhouse control using different techniques and show how
the models obtained can be exploited for simulation or control design;
they suggest ideas for the development of physical and/or black-box
models for this purpose.
Strategies for the control of climate- and irrigation-related variables
are brought forward. The uses of PID control and feedforward
compensators, both widely used in commercial tools, are summarized. The
benefits of advanced control techniques--event-based, robust, and
predictive control, for example--are used to improve on the performance
of those basic methods.
A hierarchical control architecture is developed governed by a
high-level multiobjective optimization approach rather than traditional
constrained optimization and artificial intelligence techniques.
Reference trajectories are found for diurnal and nocturnal temperatures
(climate-related setpoints) and electrical conductivity
(fertirrigation-related setpoints). The objectives are to maximize
profit, fruit quality, and water-use efficiency, these being encouraged
by current international rules. Illustrative practical results selected
from those obtained in an industrial greenhouse during the last eight
years are shown and described. The text of the book is complemented by
the use of illustrations, tables and real examples which are helpful in
understanding the material.
Modeling and Control of Greenhouse Crop Growth will be of interest to
industrial engineers, academic researchers and graduates from
agricultural, chemical, and process-control backgrounds.
