Machine-learning-based model predictive control with instantaneous linearization – A case study on an air-conditioning and mechanical ventilation system

2022 ◽  
Vol 306 ◽  
pp. 118041
Author(s):  
Shiyu Yang ◽  
Man Pun Wan
2021 ◽  
Vol 297 ◽  
pp. 117112
Author(s):  
Shiyu Yang ◽  
Man Pun Wan ◽  
Bing Feng Ng ◽  
Swapnil Dubey ◽  
Gregor P. Henze ◽  
...  

2020 ◽  
Vol 53 (2) ◽  
pp. 15771-15776
Author(s):  
Murali Padmanabha ◽  
Lukas Beckenbach ◽  
Stefan Streif

2011 ◽  
Vol 44 (1) ◽  
pp. 9266-9271
Author(s):  
Nan Yang ◽  
Dewei Li ◽  
Jun Zhang ◽  
Yugeng Xi

2010 ◽  
Vol 64 (3) ◽  
Author(s):  
Michal Kvasnica ◽  
Martin Herceg ◽  
Ľuboš Čirka ◽  
Miroslav Fikar

AbstractThis paper presents a case study of model predictive control (MPC) applied to a continuous stirred tank reactor (CSTR). It is proposed to approximate nonlinear behavior of a plant by several local linear models, enabling a piecewise affine (PWA) description of the model used to predict and optimize future evolution of the reactor behavior. Main advantage of the PWA model over traditional approaches based on single linearization is a significant increase of model accuracy which leads to a better control quality. It is also illustrated that, by adopting the PWA modeling framework, MPC strategy can be implemented using significantly less computational power compared to nonlinear MPC setups.


Author(s):  
Tobias Heidrich ◽  
Jonathan Grobe ◽  
Henning Meschede ◽  
Jens Hesselbach

The following paper describes an economical, multiple model predictive control (EMMPC) for an air conditioning system of a confectionery manufacturer in Germany. The application consists of a packaging hall for chocolate bars, in which a new local conveyor belt air conditioning system is used and thus the temperature and humidity limits in the hall can be significantly extended. The EMMPC calculates the optimum energy or cost humidity and temperature set points in the hall. For this purpose, time-discrete state space models and an economic objective function with which it is possible to react to flexible electricity prices in a cost-optimised manner are created. A possible future electricity price model for Germany with a flexible EEG levy was used as a flexible electricity price. The flexibility potential is determined by variable temperature and humidity limits in the hall, which are oriented towards the comfort field for easily working persons, and the building mass. The building mass of the created room model is used as a thermal energy store. Considering electricity price and weather forecasts as well as internal, production plan-dependent load forecasts, the model predictive controller directly controls the heating and cooling register and the humidifier of the air conditioning system.


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