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Nonlinear Model Predictive Control with aggregated constraints?
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AI
DOI：10.1016/j.automatica.2022.110649.png)
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Abstract
En 中文
This paper presents a constraint aggregation approach for Nonlinear Model Predictive Control (NMPC). Constraint aggregation functions provide an approximation of the feasible region with a reduced number of nonlinear constraints. The effect of the aggregation on the closed-loop system performance and stability is studied using tools from sensitivity analysis. Numerical results for the control of a 20th order flexible aircraft model show that significant computational savings can be achieved. The proposed method can facilitate the implementation of NMPC solutions for large-scale systems.(c) 2022 Elsevier Ltd. All rights reserved.
Keywords:
Nonlinear Model Predictive Control
Constraint aggregation
Optimization
Large-scale systems
Journal
IF:
5.9
Papers:
1.2W
Citations:
5.2W
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