Performance Adaptive Aeroeleastic Wing (PAAW) Program
Persistent link for this communityhttps://hdl.handle.net/11299/167170
The goal of the Performance Adaptive Aeroelastic Wing (PAAW) Program is to research and develop a future commercial aircraft wing that continuously optimizes its shape for current flight conditions and aircraft configuration. This approach could maximize lift for takeoff, minimize fuel consumption in cruise, or maximize lift and drag for landing. All data, models, and software developed as part of this program will be available open-source.
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Browsing Performance Adaptive Aeroeleastic Wing (PAAW) Program by Author "Danowsky, Brian"
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Item Application of MIDAAS to BFF Models(2014-11-23) Danowsky, BrianModal Isolation and Damping for Adaptive Aeroservoelastic Suppression (MIDAAS) was applied to the BFF model at various flight conditions. All available control surfaces were used with nine sensors. MIDAAS synthesis produces a gain matrix feeding back all outputs to all inputs. Using these inputs and outputs, the resulting gain matrix is 9 by 8. Solutions were obtained for 3 different flight conditions (42, 44, and 50 knots). For each flight condition, a solution was obtained for two models, 1) bare airframe dynamics and 2) full system dynamics including bare airframe, actuator and sensor dynamics.Item CFD/CSD-based IOROM Construction for mAEWing1 initial design(2015-09-15) Danowsky, BrianThis working paper summarizes the construction of the Input to Output Reduced Order Model (IOROM) for mAEWing1. The linear time invariant (LTI) IOROM is based on a fixed trimmed flight condition and is represented as a state space system with the traditional four matrix quadruple: [A, B; C, D]. These IOROMs are entirely software-based models that start with a detailed Computational Fluid Dynamic / Computational Structural Dynamic (CFD/CSD)-based model built in the CMSoft, Inc. AERO software suite. The nonlinear full order AERO model (NFOM) is millions of degrees of freedom and is unsuitable for open loop dynamic analysis and control system design. From this model, a linear time invariant reduced order aeroelastic model (ROM) is built describing the modal structural dynamics coupled with the unsteady aerodynamic forces. This model is represented in an inertial frame since that is the frame for the finite element model (FEM). This ROM is sent to the STI ASETool software where the structural rigid body states are cast into the traditional body-fixed frame, and the input and output effect is added with user defined descriptions of actuation and sensor nodes resulting in the IOROM. The IOROM is a linear model of significantly reduced order that is in the ideal form for dynamic analysis and control system design. It includes all rigid body states, structural modal states, and unsteady aerodynamic states. The 12 rigid body states include the translational and rotational displacements and velocities and are represented in their traditional body-fixed frame of reference, making this model in an ideal form for complete control system design that includes primary flight control and flutter suppression. Stability and control derivatives can be directly extracted from the IOROM for direct comparison to experimental test data or other analytical models. These models are also used for novel system analysis using phasor diagrams where rigid body and flexible dynamic coupling can be clearly characterized. Approximate linear parameter varying models can also be created from the IOROMs that are dependent on a variable trim velocity. These models can be used for traditional flutter analysis (e.g., V-G diagrams, etc.) and LPV control design.Item Classical Control Design Feasibility Study with BFF Models(2014-11-18) Lee, Dongchan; Danowsky, BrianThis working paper documents an initial control feasibility study to determine if classical control techniques could be utilized to favorably augment the stability of the BFF vehicle. This study focused on the lower speed models which have stable, or slightly unstable aeroelastic dynamics. Future studies will explore the higher speed models with highly unstable aeroelastic modes. The final control solution will incorporate stability augmentation with aeroelastic suppression, including flutter suppression to stabilize the vehicle beyond the flutter boundary. The principal goal is a defined strategy, process and supporting software tools to develop a full envelope controller for flexible aeroelastic vehicles with significant rigid body and flexible coupling. Focus will be on blended wing-body vehicle designs like the BFF and X-56A. The purpose of this study is a background feasibility investigation.Item Investigation of suitable flight test inputs for system identification of low frequency dynamics for the mini MUTT(2015-01-16) Dongchan, Lee; Danowsky, BrianThe purpose of this document is to investigate suitable excitations for flight test to identify rigid body dynamic characteristics. It is understood that the stiff wing mini MUTT (Fenrir) will be flown soon for identification of rigid body dynamic characteristic. The flight test data will further be used to identify unknown system parameters offline. The model system considered in this study is the BFF model at 40 kts as this is the lowest flight condition available and displays the least amount of coupling between rigid body and flexible dynamics. It is noted that this model still displays coupling between the pitch dynamics and the 1st symmetric wing bending mode. The objective is to focus on low frequency dynamics as it is expected that the stiff wing mini MUTT (Fenrir) should display similar low frequency dynamics. Different input sequences for the elevator and aileron control inputs, are investigated. The sensors investigated are the roll and pitch rates at the aircraft center body IMU.Item Investigation of system input and output blending for zero placement(2014-11-25) Danowsky, BrianThe zeros are a function of the system input and output. Appropriate selection of sensor outputs and control inputs influences the zeros of the open loop system and this directly influences the effectiveness of any resulting controller. The purpose of this working paper is to summarize the investigation of appropriate input and output blending for zero placement as applied to an aeroseroelastic pitch-plunge model.Item Modal Identification from Sköll flight tests(2015-06-20) Danowsky, BrianModal identification was performed on flight test data using the Curve Fitting Frequency Domain Decomposition (CFDD) method. The emphasis is to identify aeroelastic modes rather than rigid body modes. Consequently, the aeroelastic short period mode was identified in addition to several higher frequency aeroelastic modes. All of the modes identified reflect complex-valued aeroelastic modes, as opposed to real-valued dry structural modes. The following flights were used for identification: Sköll Flight 3: 20 m/s flight condition; Sköll Flight 4: 30 m/s flight condition.Item Parameter identification studies using SIDPAC with Fenrir’s 1st flight data set(2015-03-06) Dongchan, Lee; Danowsky, BrianThis document summarizes the process of identifying unknown dynamic systems from measured flight test data. Several available system identification tools were evaluated based on accuracy and robustness. Among them,SIDPAC developed by NASA was chosen. The objective of this study is to lay out the procedures to identify unknown systems from flight test data and to provide recommendations for following flight tests. Data from the Fenrir’s flight was used.Item Preliminary Open Loop Analysis of BFF Models: Concentrating on low frequency dynamics(2014-11-17) Danowsky, BrianThis working paper documents preliminary open loop analysis of the Lockheed Martin BFF models. These models were delivered to Systems Technology Inc from the University of Minnesota under a different contract. The focus for this study is on the rigid body dynamics which are in the lower frequency range. This vehicle has high coupling between rigid body and flexible dynamics so traditional classic rigid body modes do not exist. Regardless, the low speed models do exhibit some behavior familiar to traditional aircraft dynamic modes (e.g., short period, phugoid, dutch roll, roll subsidence, spiral).Item Preliminary system identification studies with the stiff wing mini MUTT Fenrir(2015-03-16) Danowsky, BrianA short successful flight test with the stiff wing mini MUTT, named Fenrir, was conducted on 9 February 2015. The purpose of this flight was to gather preliminary data for system identification focused on low frequency rigid body dynamics.Item Survey of Existing Aeroservoelastic Models(2015-05-04) Danowsky, Brian; Schmidt, DavidThis working paper documents a survey of existing mathematical models of aeroservoelastic aircraft. For the purposes of this working paper, the primary purpose of such models is for control analysis and design. Enhanced validation and simulation (piloted and non-piloted) are also important.Item System identification studies with the stiff wing mini MUTT Fenrir – Flight 20(2015-06-11) Danowsky, BrianA successful flight test with the stiff wing mini MUTT, named Fenrir, was conducted on 27 May 2015. The purpose of this flight was to gather preliminary data for system identification focused on low frequency rigid body dynamics. No augmentation was used during the 1st flight on this day, which is formally flight 20. This working paper analyzes flight 20 only. 3-2-1-1 pitch excitations were sent to individual symmetric surface pairs coincident with normal pilot inputs. For reference, a preliminary model of the stiff wing Fenrir (developed by D. K. Schmidt) at a flight condition of 65 ft/s (19.8 m/s) indicates a short period mode at 9.02 rad/s with a damping ratio of 0.658 and a phugoid mode at 0.569 rad/s with a damping ratio of -0.0251. It is expected that the actual aircraft dynamics will differ but these dynamic parameters provide a good baseline for ballpark values for comparison to the flight test data. Analysis of these data were performed in both the frequency and time domains. Short period system parameters were identified using two approaches: 1) frequency domain equation error, and 2) subspace system identification in the time domain.