Version 1
: Received: 27 February 2022 / Approved: 28 February 2022 / Online: 28 February 2022 (07:23:56 CET)
How to cite:
van Paridon, A.; Sands, T. Novel State-Space Realization Generalized from Turbine Blade Modeling. Preprints2022, 2022020348. https://doi.org/10.20944/preprints202202.0348.v1
van Paridon, A.; Sands, T. Novel State-Space Realization Generalized from Turbine Blade Modeling. Preprints 2022, 2022020348. https://doi.org/10.20944/preprints202202.0348.v1
van Paridon, A.; Sands, T. Novel State-Space Realization Generalized from Turbine Blade Modeling. Preprints2022, 2022020348. https://doi.org/10.20944/preprints202202.0348.v1
APA Style
van Paridon, A., & Sands, T. (2022). Novel State-Space Realization Generalized from Turbine Blade Modeling. Preprints. https://doi.org/10.20944/preprints202202.0348.v1
Chicago/Turabian Style
van Paridon, A. and Timothy Sands. 2022 "Novel State-Space Realization Generalized from Turbine Blade Modeling" Preprints. https://doi.org/10.20944/preprints202202.0348.v1
Abstract
Mathematical models across the applied sciences often utilize a standard methodological representation called a state variable formulation more commonly referred to as state space form. Recent research in unmanned underwater vehicle motor turbine blade thermal modeling for fatigue-life is generalized here permitting the proposed novel state space from to be applied to electrodynamics, motion mechanics, and many other disciplines. Proposed here is a very compact form inherently representing time variance, with a convenient presentation of dynamic variables applicable to all proper transfer functions, where all the distinct, real poles, zeros and gain of the transfer function appear as explicit components in the state space. The resulting manifestation simplifies utilization of the state space methods broadly across the applied sciences.
Keywords
transfer function; state-space; realization; conversion
Subject
Engineering, Mechanical Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
