Sensitivity vector fields (SVFs) have proven to be an effective method for identifying parametric variations in dynamical systems. These fields are constructed using information about how a dynamical system's attractor deforms under prescribed parametric variations. Once constructed, they can be used to quantify any additional variations from the nominal parameter set as they occur. Since SVFs are based on attractor deformations, the geometry and other qualities of the baseline system attractor impact how well a set of SVFs will perform. This paper examines the role attractor characteristics and the choices made in SVF construction play in determining the sensitivity of SVFs. The use of nonlinear feedback to change a dynamical system with the intent of improving SVF sensitivity is explored. These ideas are presented in the context of constructing SVFs for several dynamical systems.
Maximizing Sensitivity Vector Fields: A Parametric Study
Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS. Manuscript received December 10, 2012; final manuscript received December 27, 2013; published online February 12, 2014. Assoc. Editor: D. Dane Quinn.
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Sloboda, A. R., and Epureanu, B. I. (February 12, 2014). "Maximizing Sensitivity Vector Fields: A Parametric Study." ASME. J. Comput. Nonlinear Dynam. April 2014; 9(2): 021018. https://doi.org/10.1115/1.4026366
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