scholarly journals Experimental comparison of canal models for control purposes using simulation and laboratory experiments

2014 ◽  
Vol 16 (6) ◽  
pp. 1390-1408 ◽  
Author(s):  
Klaudia Horváth ◽  
Eduard Galvis ◽  
José Rodellar ◽  
Manuel Gómez Valentín

Considerable amounts of water can be saved by automating irrigation canals. The design of most of the practical automatic controllers rely on a simplified model of the irrigation canal. This model can be obtained from measured data (identification) or can be formulated (white box models) assuming simplifications in the physical concepts and using the canal geometry. Several models of this kind are presently available. Moreover, short canals reveal a resonance problem, due to the back and forth of waves. This paper is focused on how to choose a suitable model for short canal pools with the purpose of control design. Four simple models are applied to two different types (resonant and non-resonant) of short canals: First order transfer function based on the Hayami model, Muskingum model, Integrator Delay (ID), and Integrator Delay plus Zero (IDZ). Model predictive controllers are developed based on these models and they are tested numerically and experimentally in order to evaluate their contribution to the control effectiveness. The controllers based on the ID and IDZ model showed the best performance.

2021 ◽  
Author(s):  
Elizabeth LeRiche

Model Predictive Controllers (MPC) in building Heating Ventilation and Air Conditioning (HVAC) systems have demonstrated significant energy savings when compared to typical on/off controllers. MPCs require information about the building’s thermal dynamics which is challenging to model, especially for older structures without buildings specifications. This research investigates the ability to develop a grey box thermal dynamic model that can determine the net thermal dynamics, without any building construction information. Sensors were installed within a test cell to monitor the building automation system (BAS) points, and collect building element surface temperature data. The simulation program Simulink was used to develop and test iterations of grey box models. The final model, that relies solely on BAS points, is able to predict the ambient temperature for a 3-hour Prediction Window to within 1.7% accuracy. This model demonstrates the potential for more buildings to implement HVAC MPC systems with grey box thermal dynamic modeling


2021 ◽  
Author(s):  
Elizabeth LeRiche

Model Predictive Controllers (MPC) in building Heating Ventilation and Air Conditioning (HVAC) systems have demonstrated significant energy savings when compared to typical on/off controllers. MPCs require information about the building’s thermal dynamics which is challenging to model, especially for older structures without buildings specifications. This research investigates the ability to develop a grey box thermal dynamic model that can determine the net thermal dynamics, without any building construction information. Sensors were installed within a test cell to monitor the building automation system (BAS) points, and collect building element surface temperature data. The simulation program Simulink was used to develop and test iterations of grey box models. The final model, that relies solely on BAS points, is able to predict the ambient temperature for a 3-hour Prediction Window to within 1.7% accuracy. This model demonstrates the potential for more buildings to implement HVAC MPC systems with grey box thermal dynamic modeling


2007 ◽  
Vol 15 (1) ◽  
pp. 191-197 ◽  
Author(s):  
Tor A. Johansen ◽  
Warren Jackson ◽  
Robert Schreiber ◽  
Petter Tondel

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