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We develop a family of reduced-order models for the modeling and control of a flow system operating under varying fluid and actuation parameters. The parametric subspaces of the reduced-order models are formed by considering the angle between the reduced-order subspaces that span the velocity fields. This grouping is combined with a discrete switching law to form a switched dynamic system composed of a set of reduced-order models. This methodology is applied to the modeling of a lid-driven cavity under varying translation velocities and phase differentials between the upper and lower walls. It is shown that the subspace angle metric successfully partitions the parametric space and provides insight on the dominant parameters that characterize the flowfields. An open-loop simulation of the resulting switched dynamic system demonstrates its ability to capture the evolution of the flow and input parameters as it occurs in the full-order model. [ABSTRACT FROM AUTHOR]

Presents a study which proposed a novel method for the analysis of flowfields obtained from either particle image velocimetry or computational fluid dynamics. Problem framework; Application of zero mass flux actuators to experimental flow diagnostics; Results and discussion.