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Model-Based Robust Optimal Control for Layer-By-Layer Ultraviolet Processing of Composite Laminates
Author(s) -
Admu Yebi,
Beshah Ayalew,
Srikanth Pilla,
Xiaoyan Yu
Publication year - 2016
Publication title -
journal of dynamic systems measurement and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.528
H-Index - 89
eISSN - 1528-9028
pISSN - 0022-0434
DOI - 10.1115/1.4034782
Subject(s) - uv curing , curing (chemistry) , materials science , parametric statistics , layer by layer , ultraviolet , computer science , attenuation , composite number , layer (electronics) , control theory (sociology) , biological system , composite material , optics , optoelectronics , mathematics , control (management) , physics , statistics , artificial intelligence , biology
This paper first discusses some experimental verification of proposed ultraviolet (UV) radiation curing process models and then it outlines a robust process optimization and control scheme for layer-by-layer UV processing of a thick composite laminate. The experiments include UV transmission, cure kinetics, and in situ temperature measurements for UV curing of a one-dimensional (1D) composite material sample. The validated models are used to motivate how optimizing the layer-by-layer curing process can help address the challenge of maintaining through-cure due to the in-domain attenuation of the UV input during thick-part fabrication. The key insight offered is to model the layer-by-layer deposition and curing process as a multimode hybrid dynamic system with a growing spatial domain, where the interlayer hold times and the UV intensity at each layer addition can be taken as the augmented control variables to be selected optimally. Specifically, the control input is set to have feed forward and output feedback components, which act on the UV intensity at each layer and are constructed to track a reference surface temperature trajectory. The feedback gains at each layer addition are designed by posing a robust optimization problem that penalizes the sensitivity of the objective function to process uncertainties. It is illustrated using simulation analyses that augmented control with robust optimal static feedback of UV intensity at each layer and nominal optimization of the interlayer hold times gives very close tracking of a desired final cure level distribution in the presence of parametric uncertainty.

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