Desired Terminal State Concept in Model Predictive Control: A Case Study

The paper deals with an online optimization control method for dynamical processes called Model Predictive Control (MPC). It is a popular control method in industry and frequently treated in academic areas as well. The standard predictive controllers usually do not guarantee stability especially for...

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Bibliographic Details
Main Authors: František Dušek, Daniel Honc
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Control Science and Engineering
Online Access:http://dx.doi.org/10.1155/2019/5208612
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Summary:The paper deals with an online optimization control method for dynamical processes called Model Predictive Control (MPC). It is a popular control method in industry and frequently treated in academic areas as well. The standard predictive controllers usually do not guarantee stability especially for the case of short horizons and large control error penalization. Terminal state is one way to ensure stability or at least increase the controller robustness. In the paper, deviation of the predicted terminal state from the desired terminal state is considered as one term of the cost function. Effect of the stability and control quality is demonstrated in the simulated experiments. The application area for online optimization methods is very broad including various logistics and transport problems. If the dynamics of the controlled processes cannot be neglected, the optimization problem must be solved not only for steady state but also for transient behaviour, e.g., by MPC.
ISSN:1687-5249
1687-5257