期刊
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
卷 31, 期 4, 页码 918-926出版社
AMER INST AERONAUTICS ASTRONAUTICS
DOI: 10.2514/1.33079
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In this paper, we present a framework for achieving constrained optimal real-time control for large-scale systems with fast dynamics. The methodology uses the explicit solution of the model predictive control problem combined with model reduction, in an output-feedback implementation. The explicit solution of the model predictive control problem leads to online model predictive control functionality without having to solve an optimization problem at each time step. Reduced-order models are derived using a goal-oriented, model-constrained optimization formulation that yields efficient models tailored to the control application at hand. The approach is illustrated on a challenging large-scale flow problem that aims to control the shock position in a supersonic diffuser.
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