Experimentally Infused Active System Optimization - Theoretical Framework and Airborne Wind Energy Case Study

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Deodhar, N. (2018). Experimentally Infused Active System Optimization - Theoretical Framework and Airborne Wind Energy Case Study. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

This research pioneers formal combined plant and controller optimization (termed ``co-design") schemes for complex systems where accurate but expensive experiments are fused with cheap but less accurate numerical simulations. This fusion of experiments with numerical modeling tools, referred to as experimentally infused optimization, addresses several challenges faced in co-design research. These challenges include strong coupling between the controller and plant, significant modeling uncertainties (which require the use of experiments), and high experimental costs. This research presents two unique iterative experimentally infused optimization approaches: One approach uses small ``batches" of experiments at each iteration to identify the gradient of a performance index, whereas the other approach leverages tools from optimal design of experiments and hypothesis testing to efficiently explore and reduce the design space at each iteration. Both approaches incorporate a model correction term that improves the numerical model prediction after each set of experiments. For the latter approach, an original theoretical convergence bound on the numerical model improvement in the presence of noise-influenced experiments is presented and derived in this dissertation. Furthermore, both approaches have been validated for performance-critical parameters on a lab-scale airborne wind energy (AWE) system test platform at UNC Charlotte. Dimensional analysis has been used to show that this unique lab-scale platform produces results that replicate the full-scale flight behavior under uniformly-scaled system time constants. Overall, the quality of flight for the AWE system is greatly improved using experimental infusion as compared to a pure numerical optimization approach.

Details
Author

Deodhar, Nihar

Title

Experimentally Infused Active System Optimization - Theoretical Framework and Airborne Wind Energy Case Study

Physical Description

1 online resource (87 pages) : PDF

Date

2018

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

This research pioneers formal combined plant and controller optimization (termed ``co-design") schemes for complex systems where accurate but expensive experiments are fused with cheap but less accurate numerical simulations. This fusion of experiments with numerical modeling tools, referred to as experimentally infused optimization, addresses several challenges faced in co-design research. These challenges include strong coupling between the controller and plant, significant modeling uncertainties (which require the use of experiments), and high experimental costs. This research presents two unique iterative experimentally infused optimization approaches: One approach uses small ``batches" of experiments at each iteration to identify the gradient of a performance index, whereas the other approach leverages tools from optimal design of experiments and hypothesis testing to efficiently explore and reduce the design space at each iteration. Both approaches incorporate a model correction term that improves the numerical model prediction after each set of experiments. For the latter approach, an original theoretical convergence bound on the numerical model improvement in the presence of noise-influenced experiments is presented and derived in this dissertation. Furthermore, both approaches have been validated for performance-critical parameters on a lab-scale airborne wind energy (AWE) system test platform at UNC Charlotte. Dimensional analysis has been used to show that this unique lab-scale platform produces results that replicate the full-scale flight behavior under uniformly-scaled system time constants. Overall, the quality of flight for the AWE system is greatly improved using experimental infusion as compared to a pure numerical optimization approach.

Genre

doctoral dissertations

Subjects--Topics

Mechanical engineering
Engineering

Degree

Ph.D.

Keywords

Airborne Wind Energy
Control Systems Engineering
Design Optimization
Dynamics
Experimental Characterization

Subject Area

Mechanical Engineering

Advisor(s)

Vermillion, Christopher

Committee Members

Kelly, Scott
Tkacik, Peter
Kakad, Yogendra
Hong, Tao

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2018.

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Rights Holder Information

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Identifier

Deodhar_uncc_0694D_11802

Permalink

http://hdl.handle.net/20.500.13093/etd:663