M.Ing. / This research project is dedicated to the automation of environmental control within greenhouses. To create an optimal climate in the greenhouse, the main environmental parameters that need to be controlled are temperature, humidity and light intensity. As a result of process dead times and the extreme interdependence of these parameters, the control problem can be classified as non-linear and multi-variable. In the past, most greenhouse environmental control systems depended on the decision making of an experienced human operator. This often gave rise to trial and error, especially when new species were established. With the current advances in "intelligent" control systems and high accuracy sensors, more and more of the decisions involved in greenhouse control can be automated. In this way more emphasis can be placed on emulating the abilities of an expert operator, by means of a computerbased automatic control system. In this research project, "intelligent" as well as "non-intelligent" control techniques, for addressing the problem of automated climate control in a greenhouse, are investigated. These include PID-control as a "non-intelligent" technique, and rule-based fuzzy logic control and self-learning fuzzy logic control as two "intelligent" control techniques. These techniques are all applied to experimental greenhouse which is equipped with management mechanisms, such as fans, heaters, sprinklers and lights. The results of the experiments are evaluated according to two performance parameters: the Control Performance Index (CPI) and the Mean Square Error (MSE). The three techniques are not only assessed for their efficiency, but also for their applicability to the greenhouse environmental problem. Each of the control techniques has a unique characteristic response to the non-linear, non-stationary, multi-variable problem of environmental control and are subsequently addressed in the respective chapter.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:8949 |
| Date | 08 August 2012 |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
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