Climate control in greenhouse using intelligent control algorithms

Greenhouse climate control problem has received considerable attention in agriculture engineering research. The greater part of accomplishing ensured farming within the greenhouse environment is achieved by controlling the temperature and relative humidity. As the result of process dead times and extreme interdependence of these parameters, the control problem is classified to be non-linear and multivariable. With the advances in intelligent control systems, more and more decisions involved in greenhouse control can be automated. Thus, more emphasis can be placed on emulating the abilities of the expert operator. In this paper, intelligent and non-intelligent control techniques for addressing the problem of automated climate control in a greenhouse are investigated. These include proportional-integral-derivative (PID) and Linear-Quadratic regulator (LQR) as a `non-intelligent' technique and fuzzy PID and fuzzy immune PID as `intelligent' technique. The new study is made for implementing the nonlinear fuzzy immune PID controller for greenhouse climate control. This controller has a simple structure and its parameters can be conveniently adjusted. It consists of a PID controller and a basic immune proportional controller in cascaded connection, the nonlinear function of the immune proportional controller is realized using fuzzy reasoning. Thus, controller parameters are adjusted online by the rules of immune feedback controller and fuzzy controller. The simulation results are compared for the effectiveness and applicability to greenhouse environmental problem.