Multivariable model predictive control of a solid substrate pilot bioreactor: A simulation study

Author(s):  
Harold Paján ◽  
Ricardo Pérez-Correa ◽  
Iván Solar ◽  
Eduardo Agosin
2014 ◽  
Vol 29 (02) ◽  
pp. 105-113 ◽  
Author(s):  
Kalpesh Patel ◽  
Elvira M. Aske ◽  
Morten Fredriksen

1994 ◽  
Vol 59 (3) ◽  
pp. 731-742 ◽  
Author(s):  
MASAHIRO OHSHIMA ◽  
IORI HASHIMOTO ◽  
HIROMU OHNO ◽  
MAKOTO TAKEDA ◽  
TAKASHI YONEYAMA ◽  
...  

Processes ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 265 ◽  
Author(s):  
Shiquan Zhao ◽  
Anca Maxim ◽  
Sheng Liu ◽  
Robin De Keyser ◽  
Clara Ionescu

This paper presents an extensive analysis of the properties of different control horizon sets in an Extended Prediction Self-Adaptive Control (EPSAC) model predictive control framework. Analysis is performed on the linear multivariable model of the steam/water loop in large-scale watercraft/ships. The results indicate that larger control horizon values lead to better loop performance, at the cost of computational complexity. Hence, it is necessary to find a good trade-off between the performance of the system and allocated or available computational complexity. In this original work, this problem is explicitly treated as an optimization task, leading to the optimal control horizon sets for the steam/water loop example. Based on simulation results, it is concluded that specific tuning of control horizons outperforms the case when only a single valued control horizon is used for all the loops.


2021 ◽  
Vol 249 ◽  
pp. 114851
Author(s):  
Yuhang Wang ◽  
Haotian Li ◽  
Huimin Feng ◽  
Kuihua Han ◽  
Suoying He ◽  
...  

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