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3rd Thermal and Fluids Engineering Conference (TFEC)

ISSN: 2379-1748

DEVELOPMENT OF P- PD- AND PID-FUZZY SISO CONTROLLERS OF A SUB-SCALED MULTI-ROOM BUILDING TEST-BED

J. Baltazar
California State University–Los Angeles, Los Angeles, CA, 90032, USA

A. Yarian
California State University–Los Angeles, Los Angeles, CA, 90032, USA

Arturo Pacheco-Vega
Hydronics Laboratory, Department of Aerospace and Mechanical Engineering University of Notre Dame, Notre Dame, IN 46556, USA; Department of Mechanical Engineering ECST A-410; California State University–Los Angeles, Los Angeles, CA, 90032, USA

DOI: 10.1615/TFEC2018.env.021805
pages 785-795


KEY WORDS: Fuzzy control, multi-room building, experimental analysis, temperature control

Abstract

We develop intelligent control strategies for thermal control in a sub-scaled multi-room building. The objective is to maintain a specific temperature in each of the rooms of the building. The controllers are built upon the fuzzy logic technique [27, 28]. Linguistic variables and if-then rules, which describe the behavior of the system, are quantified –respectively– by triangular membership functions and data obtained for different operating conditions. Each room is a closed loop SISO system with a Mamdani inference method [13], used to defuzzify the outputs. The control variables are the averaged temperatures inside the rooms, whereas the manipulated ones are the flow rates of the airflow. The test-bed has 8 rooms, distributed in 2 floors. A cooling unit provides cold air to the system, whereas 25 W light bulbs act as a heat load in each room. Two K-type thermocouples, placed in each room, gather temperature-readings, and dampers are designed to control the airflow delivered by the cooling unit into each. Temperature readings and control actions are performed via LabVIEW, and MATLAB is used to implement the fuzzy controllers, while experiments are conducted to assess their relative performance. Results demonstrate that all fuzzy controllers can effectively maintain the temperature of each room within ±1°C of the setpoint, although the PID-based control is the most efficient.

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