Configurable Parametric Aeroservoelastic Reduced-Order Models for Aerostructural Sensing and Control

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 team present a considerable opportunity to extract dominant aerodynamic, structural dynamics, and control surface effects in a compact form that can be used to evaluate and optimize controllers for suppression of flutter and gust loads. The Phase I effort focused on development of the data generation, ROM training, and control synthesis workflow. The Phase I capability was demonstrated using ASE problems of interest to NASA (e.g., suppression of gust response and flutter). The Phase II efforts will focus on: (1) refinement of the aeroelastic simulation process for improved training and verification; (2) addition of late-breaking ROM techniques for improved characterization of the aeroelastic system; (3) implementation of more complex control schemes, sensor models, and actuator models to assess whether ROMs can be used for case studies with increased realism; and (4) extensive software validation and demonstration for ASE and flight control design of realistic aircraft of interest to NASA. The capabilities will be provided as a modular software environment for integration into NASA workflow for technology transition. Modern concept air vehicles are increasingly examining utilization of lightweight and flexible structures that push aeroelastic limits to achieve enhanced maneuverability, endurance, and performance. Aerostructural controllers are critical to both suppressing instabilities and gainfully exploiting aeroelastic phenomena over broad flight envelopes. Modeling and simulation considerably improve our understanding of aeroelastic systems. Unfortunately, techniques, like computational fluid and structure dynamics (CFD and CSD), are not particularly well-suited to control design. The computational cost and speed mismatch render CFD and CSD impractical for use in the design and control environment. Therefore, the ability to consider the aeroelastic content and phenomena captured through CFD and CSD simulations within controller design processes at a faster rate is needed. Recognizing this opportunity, we proposed development of a framework for configurable parametric reduced order models (ROMs) for development of novel aeroservoelastic sensing and control approaches. The overarching objective of this project is to develop a tool with the ability to affordably incorporate high-fidelity aeroelastic effects into control and sensing approaches by leveraging reduced-order models (ROMs). The Phase 1 effort provided a compelling proof-of-concept that ROMs could be trained to accurately represent CFD simulation data and then used as plant models to inform sensor placement and controller synthesis. The Phase 2 effort will build upon these accomplishments and extend the capability of the framework. Specific Phase 2 technical objectives are: 1) extend the data generation process to provide more information to the downstream modules for reduced-order modeling, sensor placement, and control scheme development; 2) extend the ROM module to support additional techniques for modeling dynamic systems; 3) refine the representation of sensors and actuators; 4) Refine the current controller development module; 5) implement control methodologies to assess whether ROMs can be utilized to support a wider range of control schemes; 6) integrate the capabilities within the modular software and improve code cohesion to support technology insertion and transition; and 7) validate and demonstrate the  framework for configurations of NASA relevance and increasing complexity. Reports and briefings will be delivered, along with the prototype ROM software.

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, SUGAR, and QueSST will benefit from the technology. The non-NASA applications are vast, and will focus on aerospace, defense, 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

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