Open AccessNeural Network System Identification and Controlling of Multivariable System
Author(s) -
Halima Begum,
P. Revathi,
D Babiyola.
Publication year - 2012
Publication title -
international journal of electronic signal and systems
Language(s) - English
Resource type - Journals
ISSN - 2231-5969
DOI - 10.47893/ijess.2012.1030
Subject(s) - multivariable calculus , greenhouse , identification (biology) , artificial neural network , mimo , process (computing) , transfer function , system identification , control theory (sociology) , computer science , control engineering , control system , system model , control (management) , engineering , data mining , artificial intelligence , agronomy , ecology , telecommunications , biology , channel (broadcasting) , electrical engineering , software engineering , measure (data warehouse) , operating system
Most of the industrial processes are multivariable in nature. Here Greenhouse system is considered which is the important application in agricultural process. Greenhouse is to improve the environmental conditions in which plants are grown .In this paper we have proposed identification of greenhouse system using input and output data sets to estimate the best model and validate the model. For MIMO systems, Neural Network System identification provides a better alternative to find their system transfer function. The results were analyzed and the model is obtained. From this obtained model ,the system is controlled by conventional method. By these method we can identify the model and control the complicated systems like Greenhouse.