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In this work, we demonstrated how model predictive control (MPC) can effectively manipulate a highly nonlinear foil-and-flap system to follow designated lift trajectories to sub-5% error. The surrogate model is built through a data-driven method merging fluidic and structural information which can be readily deployed to numerous fluid-structure interaction systems. The rapid optimization procedure utilized to generate the control signal can also be used for estimating ambient environmental change
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Wang et al. (2024) studied this question.
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