期刊
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
卷 30, 期 1, 页码 100-120出版社
WILEY
DOI: 10.1002/rnc.4754
关键词
bioreactor; min-max problem; robust model predictive control; stability; uncertain systems
This work deals with the problem of trajectory tracking for a nonlinear system with unknown but bounded model parameter uncertainties. First, this work focuses on the design of a robust nonlinear model predictive control (RNMPC) law subject to model parameter uncertainties implying solving a min-max optimization problem. Secondly, a new approach is proposed, consisting in relating the min-max problem to a more tractable optimization problem based on the use of linearization techniques to ensure a good trade-off between tracking accuracy and computation time. The developed strategy is applied in simulation to a simplified macroscopic continuous photobioreactor model and is compared to the RNMPC and nonlinear model predictive controllers. Its efficiency and its robustness against parameter uncertainties and/or perturbations are illustrated through numerical results.
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