Date of Award

Fall 2019

Document Type


Degree Name

Master of Science (MS)


Electrical and Computer Engineering

First Advisor

Yaz, Edwin E.

Second Advisor

Schneider, Susan

Third Advisor

Bonniwell, Jennifer


In this thesis model order reduction techniques are applied to a set of systems representing the thermodynamics of a multi-zone building. The models are intended to be used in a model predictive control (MPC) application, with the individual zones defined using a simplified two temperature model. There has been an increased interest in model identification and reduction for MPC applications of building models that include multi-zone and non-linear models, but the most of this work has focused on models where individual zones are represented with a higher order model. Manual pole/zero removal, dominant eigenvalue, and balanced model reduction methods are presented, along with a proposed application specific method that takes advantage of the zone model’s simplified form. The proposed method treats a set of the zones as a common airspace with comparable control and reduces the underlying resistor/capacitor (RC) network. These methods are applied to a two zone and a six zone model with various coupling configuration tested. The general form of the multi-zone model proves difficult to reduce without making modification to the original form. The effects of reducing the inputs and outputs, through methods such as using a common temperature setpoint, are presented with significant improvements to reduction capabilities. Balanced model reduction the 18th order system down to 9th and 5th based on which inputs and outputs are reduced, and the application specific methods is able to reduce the same system down to a 3rd order model when the inputs and outputs are fully reduced.

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Engineering Commons