Modeling and controller design for heating and ventilation control system using system identification approach

Abstract

System modeling is an important task to develop a mathematical model that describes the dynamics of a system. The scope of work for this project consists of modeling and controller design for a particular system. A heating and ventilation model VVS-400 from Instrutek, Larvik, Norway is the system to be modeled and will be perturbed by pseudo random binary sequences (PRBS) signal. Parametric approach using ARX model structure will be use to estimate the mathematical model or approximated model plant of the VVS-400. The approximated plant model is estimated using System Identification approach. The conventional PID controller and artificial Fuzzy controller are designed based on the approximated plant model and also real plant model where the real plant model is developed by interfacing the Real-time Windows Target toolbox in Matlab with real VVS-plant by using data acquisition (DAQ) card PCI-1711. An artificial Fuzzy controller approach is incorporated in two ways which are conventional Fuzzy logic controller (FLC) and a replacement of conventional fuzzy controller known as Single Input Fuzzy Logic Controller (SIFLC). Simulations and experiment validate the equivalency of both controllers. Results reveal that SIFLC found to be better than FLC due to its less computation time compared to conventional FLC.