<p> The design of control mixing algorithms for launch vehicles with multiple vectoring engines yields competing objectives for which no straightforward solution approach exists. The designer seeks to optimally allocate the effector degrees of freedom such that maneuvering capability is maximized subject to constraints on available control authority. In the present application, such algorithms are generally restricted to linear transformations so as to minimize adverse control-structure interaction and maintain compatibility with industry-standard methods for control gain design and stability analysis. Based on the application of the theory of ellipsoids, a complete, scalable, and extensible framework is developed to effect rapid analysis of launch vehicle capability. Furthermore, a control allocation scheme is proposed that simultaneously balances attainment of the maximum maneuvering capability with rejection of internal loads and performance losses resulting from thrust vectoring in the null region of the admissible controls. This novel approach leverages an optimal parametrization of the weighted least squares generalized inverse and exploits the analytic properties of the constraint geometry so as to enable recovery of more than ninety percent of the theoretical capability while maintaining linearity over the majority of the attainable set.</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:3561548 |
| Date | 21 June 2013 |
| Creators | Orr, Jeb S. |
| Publisher | The University of Alabama in Huntsville |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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