Multivariable parametric modeling of a greenhouse by minimizing the quadratic error

Abstract

This paper concerns the identification of a greenhouse described in a multivariable linear system with two inputs and two outputs (TITO). The method proposed is based on the least squares identification method, without being less efficient, presents an iterative calculation algorithm with a reduced computational cost. Moreover, its recursive character allows it to overcome, with a good initialization, slight variations of parameters, inevitable in a real multivariable process. A comparison with other methods recently proposed in the literature demonstrates the advantage of this method. Simulations obtained will be exposed to showthe effectiveness and application of the method on multivariable systems.