The goal of the proposed effort is to develop a framework for configurable reduced-order modeling (ROM) for the development of novel aeroservoelastic (ASE) sensing and control approaches within a broad flight parameter space. Parametric ROM techniques developed by the proposing teams present a considerable opportunity to extract dominant aerodynamic and structural dynamics in a compact form that can be used to evaluate and optimize controllers for suppression of flutter and gust loads. This Phase I effort is focused on facilitating ROM technology adoption by ASE control engineers in NASA by providing (1) ROM techniques cast within a genetic algorithm and superposable platform for automated development of configurable, state-consistent ROMs and (2) the ability to apply the configurable ROMs for design and evaluation of aerostructural controllers. These components will be integrated within a modular software framework to streamline the entire workflow and efficiently transition from the model reduction to control synthesis. In Phase I, the feasibility of the proposed technology will be demonstrated for ASE problems of NASA interest (e.g., suppression of gust response and flutter). The Phase II efforts will focus on: (1) optimization of the ROM and control synthesis modules in terms of execution efficiency, robustness, and autonomy; (2) further process automation and exact input/output formatting for direct integration of the framework into NASA’s controller development workflow; and (3) extensive software validation and demonstration for ASE and flight control design of realistic aircraft of current interest to NASA
This research will deliver NASA a valuable tool to automate ASE ROM and control synthesis; design advanced aerostructural controllers; and perform real-time ASE simulation; and will markedly improve the process for considering aeroelasticity in controller development through rapid predictions of gust loads, ride quality, and stability and control issues. It will significantly decrease simulation validation and workflow lag time, reduce development costs and time. NASA projects like MUTT, MADCAT, and QueSST will benefit from the technology
The non-NASA applications are vast, and will focus on aerospace, aircraft, and watercraft engineering for fluid-structural interaction and fatigue analysis, control and optimization, hardware-in-the-loop simulation, and others. The proposed development will provide a powerful tool which can be used for fault diagnostics, optimized design, simulation and experiment design and planning, and more.