An Intelligent Framework to Develop Adaptive Parametric Reduced Order Model Database for Aerostructural Control

The goal of the project is to develop an intelligent framework to construct adaptive parametric reduced order model (PROM) database for aeroservoelastic (ASE) analysis and aerostructural control. In Phase 1, the framework for both equation-based and data-driven PROMs was developed and feasibility to introduce ldquo;engineering intelligencerdquo; to AE/ASE ROMs was successfully established. Carefully selected ROMs and intelligence algorithms were developed to accomplish autonomous PROM construction. It was verified that ROMs built under the guidance of intelligent algorithms enable unprecedented state consistence and computational performance. For the first time, data-driven ROMs with state consistence were developed in a broad flight envelope. Equation-based ASE PROMs were developed, and demonstrated gt;12X reduction in model size for control synthesis. In Phase 2, software will be further refined for enhanced performance and functionality. Genetic Algorithm (GA)-guided ROM algorithms will be improved in terms of search space exploration, meta-optimization, and state consistence. Adaptive sampling will be extended to multi-dimensional flight parameter space. Methods to integrate PROMs from separate domains, and sensors and controllers will be optimized to meet various needs in NASA. A modular intelligent environment will be integrated into NASA workflow for technology transition. The software will be extensively validated and demonstrated for automated ROM development, certification, and control design using flexible vehicles of NASA interest.