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research-article

EXPERIMENTALLY INFUSED PLANT AND CONTROLLER OPTIMIZATION USING ITERATIVE DESIGN OF EXPERIMENTS - THEORETICAL FRAMEWORK AND AIRBORNE WIND ENERGY CASE STUDY

[+] Author and Article Information
Nihar Deodhar

Univ. of North Carolina at Charlotte Charlotte, North Carolina 28223
ndeodhar@uncc.edu

Joseph Deese

Univ. of North Carolina at Charlotte Charlotte, North Carolina 28223
jdeese23@uncc.edu

Christopher Vermillion

Univ. of North Carolina at Charlotte Charlotte, North Carolina 28223
cvermill@uncc.edu

1Corresponding author.

ASME doi:10.1115/1.4037014 History: Received December 20, 2016; Revised June 01, 2017

Abstract

This research presents an iterative framework for optimizing the plant and controller for complex systems by fusing expensive but valuable experiments with cheap yet less accurate simulations. At each iteration, G-optimal design is used to generate experiments and simulations within a prescribed design space that is shrunken in size after each successful iteration. The shrinking of the design space is determined through statistical characterization of a response surface model, and further shrinking is achieved at successive iterations through a numerical model correction factor that is driven by the results of experiments. An initial validation of this iterative design optimization framework was performed on an airborne wind energy system, where tethers and an aerostat are used in place of a tower to elevate the turbine to high altitudes. Using a unique lab-scale setup for the experiments, the aforementioned iterative methodology was used to optimize the center of mass location and pitch angle set-point for the airborne wind energy system. The optimum configuration yielded a substantial improvement in system responses as compared to a numerically optimized configuration. The framework was recently extended to include four variables (horizontal and vertical stabilizer areas, center of mass location, and pitch angle set-point).

Copyright (c) 2017 by ASME
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