Integrated Robust Optimal Design (IROD) via sensitivity minimization

dc.contributor.advisor Atul G. Kelkar
dc.contributor.author Tulpule, Punit
dc.contributor.department Mechanical Engineering
dc.date 2018-07-20T22:19:54.000
dc.date.accessioned 2020-06-30T02:53:44Z
dc.date.available 2020-06-30T02:53:44Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2014
dc.date.embargo 2015-07-30
dc.date.issued 2014-01-01
dc.description.abstract <p>A novel Integrated Robust Optimal Design (IROD) methodology is presented in this</p> <p>work which combines a traditional sensitivity theory with relatively new dvancements</p> <p>in Bilinear Matrix Inequality (BMI) constrained optimization problems. IROD provides</p> <p>the least conservative approach for robust control synthesis. The proposed methodology is demonstrated using numerical examples of integrated control-structure design problem for combine harvester header and excavator linkages. The IROD methodology is compared with the state of the art sequential design method using the two application examples, and the results show that the proposed methodology provides a viable alternative for robust controller synthesis and often times offers even a better performance than competing methods. Although this method requires linearization of nonlinear system at each system parameter optimization step, a technique to linearized Differential Algebraic Equations (DAE) is presented which allows use of symbolic approach for linearization. This technique avoids repetitive linearizations. For the nonlinear systems with parametric uncertainties which can not be linearized at operating points, a new methodology</p> <p>is proposed for robust feedback linearization using sensitivity dynamics-based formulation. The feedback linearization approach is used for systems with augmented sensitivity dynamics and used to refine control input to improve robustness. The method is demonstrated using an example of a position tracking control of a hydraulic actuator. The robustness of controller design is demonstrated by considering variations in fluid density parameter. The results show that the proposed methodology improves robustness of the feedback linearization to parametric variations.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/14011/
dc.identifier.articleid 5018
dc.identifier.contextkey 6199738
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/14011
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/28198
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/14011/Tulpule_iastate_0097E_14427.pdf|||Fri Jan 14 20:12:12 UTC 2022
dc.subject.disciplines Mechanical Engineering
dc.subject.keywords Control systems
dc.subject.keywords Feedback linearization
dc.subject.keywords Integrated design
dc.subject.keywords LMI
dc.subject.keywords Multibody dynamics
dc.title Integrated Robust Optimal Design (IROD) via sensitivity minimization
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication 6d38ab0f-8cc2-4ad3-90b1-67a60c5a6f59
thesis.degree.level dissertation
thesis.degree.name Doctor of Philosophy
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