Advanced controllers for building energy management systems. Advanced controllers based on traditional mathematical methods (MIMO P+I, state-space, adaptive solutions with constraints) and intelligent solutions (fuzzy logic and genetic algorithms) are investigated for humidifying, ventilating and air-conditioning applications.

This thesis presents the design and implementation of control strategies for building energy management systems (BEMS). The controllers considered include the multi PI-loop controllers, state-space designs, constrained input and output MIMO adaptive controllers, fuzzy logic solutions and genetic algorithm techniques. The control performances of the designs developed using the various methods based on aspects such as regulation errors squared, energy consumptions and the settling periods are investigated for different designs. The aim of the control strategy is to regulate the room temperature and the humidity to required comfort levels. In this study the building system under study is a 3 input/ 2 output system subject to external disturbances/effects. The three inputs are heating, cooling and humidification, and the 2 outputs are room air temperature and relative humidity. The external disturbances consist of climatic effects and other stochastic influences. The study is carried out within a simulation environment using the mathematical model of the test room at Loughborough University and the designed control solutions are verified through experimental trials using the full-scale BMS facility at the University of Bradford.

Grantor dc:publisher.institution

University of Bradford

Year dc:date.issued

2010

Author dc:creator

• Ghazali, Abu Baker MHD.

Advisor dc:contributor.advisor

• Virk, G.S.

• Air-conditioning
• Ventilation
• Advanced controllers
• Building energy management systems
• Humidification
• Mathematical solutions
• Intelligent solutions
• Multi-input/multi-output (MIMO) systems
• Multivariable P+I controllers
• State-space methods
• Modal control
• Constrained adaptive control
• Fuzzy logic controllers
• Genetic algorithms

Statement dc:rights

• <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/10454/4197

OAI identifier oai:identifier

oai:bradscholars.brad.ac.uk:10454/4197