Document
National Aeronautics and Space Administration
Flight Control of Flexible Aircraft
Dr. Nhan Nguyen Technical Group Lead Advanced Control and Evolvable Systems (ACES) Group Intelligent Systems Division NASA Ames Research Center Moffett Field, CA NESC GNC Meeting at NASA ARC January 25, 2017
Outline
• Introduction • Performance Adaptive Aeroelastic Wing • Aeroservoelasticity Modeling of Flexible Aircraft • Multi-Objective Flight Control – Real-Time Drag Minimization – Gust / Maneuver Load Alleviation – Adaptive Flutter Suppression • X-56A Collaboration • Other Collaborations
Advanced Control and Evolvable Systems Group
• Advanced Control and Evolvable Systems (ACES) Group within the Intelligent Systems Division (code TI) has 21 researchers, 13 with Ph.D.
• Conduct GNC research and multidisciplinary fixed-wing vehicle dynamic modeling and simulations • More than 90% research supports aeronautics with some space-related GNC
Introduction
• Composite wing technology in modern passenger aircraft affords weight reduction but also causes increased wing flexibility Composite Airframe N+3 Aircraft High-Aspect Ratio Truss-Braced Wing Boeing 787 Copyright © Boeing
Impact on Aerodynamics
• Increased wing deflection impacts optimal span load at off-design, causing increase in drag Increased drag leads to increased fuel consumption
Impact on Flight Load, Stability and Control
• Increased wing flexibility causes reduced flutter margin, aeroservoelastic interactions with dynamics and control, and increased gust response Aspect Ratio High Low
Performance Adaptive Aeroelastic Wing Research
• Multidisciplinary design analysis optimization (MDAO) capabilities for development of advanced adaptive wing technology concepts Control Effectors Mul<-Fidelity Modeling ASE – Flight Dynamics • VCCTEF / con6nuous leading • Mul6-fidelity aero modeling (Cart3D, • Coupled ASE – rigid aircraL flight edge slat Overflow, Lava, Vorlax , Vspaero ) dynamics • Distributed control surfaces • Coupled FEM (Beam3D, NASTRAN) with • Gust modeling • Other novel concept aero codes • Actuator dynamics of ASE control • Aeroelas6city / Aeroservoelas6city (ASE) effectors Mul<disciplinary Op<miza<on Performance Analysis ASE Flight Control • Aerodynamic design op6miza6on for • Design trade-study • ASE control (fluGer suppression, drag reduc6on • Mission analysis / trajectory load allevia6on) • MDO for drag minimiza6on, load op6miza6on to minimize fuel • mul6-objec6ve flight control allevia6on, and ac6ve ASE control burn • Real-6me drag op6miza6on
Performance Adaptive Aeroelastic Wing
• Variable Camber Continuous Trailing Edge Flap (VCCTEF) developed by NASA and Boeing Research & Technology as adaptive wing control technology for drag reduction Multi-Segment Variable Camber SMA and EMA Hinge Line Actuation Individual Flap Deflection for Spanwise Lift Optimization Conformal Mold Line Material for Gap Covering to Eliminate Flap Noise and Reduce Drag
Flexible Wing High-Aspect Ratio Transport Models
• Flexible conventional transport and next-generation Truss Brace Wing NASA Generic Truss-Braced Wing Transport Model Aircraft (TBW) (GTM) • VCCTEF is equipped as an adaptive wing control technology 19 Flaps (4 Inboard, 10 Flaps, 2 Camber 15 Outboard), 3 Segments per Flap Camber Segments per Flap
Multi-Fidelity Coupled Aerodynamic Tools
• Right fidelity tools – Euler and high-fidelity RANS CFD for optimization and vortex-lattice with transonic and viscous flow corrections for MDAO OVERFLOW Static Aero-Structure LAVA CFD CART3D Static Aero-Structure VORLAX Static & Dynamic FEM / NASTRAN
Drag and Maneuver Load Control Optimization
• Drag and maneuver load minimization with VCCTEF Coupled FEM-VORLAX Load Alleviation Optimization CART3D Aero-Structural Drag Minimization Flapwise Wing Bending Moment Clean Wing Optimized w/ VCCTEF ~ 1% - 4% Drag Reduction ~ 40% Bending Moment Reduction
Aeroservoelasticity
• Gust and maneuver load responses are important design considerations for flexible wing transports • Integrated coupled ASE flight dynamics provides flight prediction capability of combined flexible vehicle stability and control response characteristics
Integrated Coupled ASE Tool
• Integrated coupled ASE tool can rapidly generate nonlinear and linear ASE state space models with gust models and with transonic and viscous corrections
Simulations of Gust Response of Truss-Braced Wing
Multidisciplinary Flight Control
• ASE flight control enables both adaptive wing performance and safe flight operation • Increased aircraft performance can be realized by addressing multidisciplinary interactions in flight control design • Integrated adaptive wing design by incorporating flight control in the MDAO cycle for weight and drag reduction
Multi-Objective Flight Control
• Multi-objective flight control, first introduced in 2012, takes advantage of multi-functional flight control surfaces such as VCCTEF to allow new capabilities in flight control to achieve multiple objectives simultaneously
ASE State Space Model
• ASE state space model with gust disturbance
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• Output equation for accelerometers • Drag model • Wing root bending moment measurement Strain Gauge Accelerometers
Multi-Objective Optimal Control
• Multi-objective cost function Pilot Command Tracking ASE Mode Suppression Drag Minimization Load Alleviation • Drag minimization and load alleviation multi-objective optimal control
Adaptive Gust Estimation
• Kalman filter state estimation of flexible aircraft dynamics • Plant modeling error • Wing root bending moment estimation error • Least-squares gradient adaptive gust estimation
Real-Time Adaptive Drag Minimization Control
• Real-time drag minimization is a technology that can truly harvest full potential of adaptive aeroelastic wing technology Fiber Optics Strain Gauge / Load Cell Fuel Flow Sensor New Sensor Technology Flap Input Real-Time Model Identification by Recursive Least-Squares Off-Design No Flap Off-Design with Flap Real-Time Drag Minimization at Off- Design
Adaptive Drag Optimization Wind Tunnel Test
• A wind tunnel test will be conducted in University of Washington Aeronautical Laboratory (UWAL) in FY17 to demonstrate adaptive drag optimization technique • Wind tunnel model will be a flexible CRM (Common Research Model) wing with 10% wing tip deflection
Wind Tunnel Tests
• Two wind tunnel tests conducted in University of Washington Aeronautical Laboratory (UWAL) in August 2013 and July 2014 Cruise Configuration Test in FY13 5% L/D Improvement ~ 6% Drag Reduction High-Lift Test in FY14
UWAL Test of Cruise Configuration
Flight Path Angle Control with Drag Minimization
Wing Tip Deflection Flight Path Angle Drag Coefficient L/D 1.25% L/D Improvement
2.5 g Pull-Up Pitch Rate Control with Load Alleviation
Wing Tip Deflection Pitch Rate Drag Coefficient Wing Root Bending Moment
Pareto Frontier Multi-Objective Optimization Analysis
Design 1 provides best compromise between drag minimization and load alleviation Design 1 Design 3 Design 2
Multi-Objective Flight Control Simulations
Adaptive Maneuver Load Alleviation
• Many physical plants are designed to meet performance specifications or constraints. For example, aircraft wing structures are designed to meet certain load limits which cannot be exceeded in-flight.
• Conventional adaptive control generally does not take into account performance optimality.
• Physical plant performance optimization can achieve performance objective.
• Adaptive control with performance optimization has been developed in connection with time-varying modification of reference model
Adaptive Maneuver Load Alleviation
• Simulations of flexible wing transport aircraft Original Ref. Model Response Performance Optimizing Ref. Model Wing Root Bending Moment Pitch Rate
Adaptive Flutter Suppression
• Aeroelastic uncertainty can degrade ASE flutter suppression control • Adaptive control could be used to improve robustness to uncertainty – leverage previous adaptive flight control work on F-18 with Optimal Control Modification with NASA AFRC Flight Test of Optimal Control Modification in 2010 • Adaptive Linear Quadratic Gaussian control
Flutter Animation
Flutter Suppression Animation
X-56A Flight Control Collaboration
• Collaboration with AFRC on X-56A flight control validation of ASE flutter suppression and multi-objective flight control – POC: Steve Jacobson and Matt Boucher – AFRC sent ARC X-56A simulations on January 23, 2016 for control development X-56A with Interchangeable Wings
X-56A Model
• Reduced-order model for longitudinal dynamics – 214 states including 5 rigid-body states , elastic and lag states for 25 elastic modes, and sensor and actuator dynamics – 16 outputs and 5 symmetric inputs including 1 body flap and 4 wing flaps per wing • Reduced-order reference model only includes 5 elastic modes and no sensor and actuator dynamics
Adaptive Augmentation
• LQR design for flight path angle control with adaptive augmentation for matched uncertainty x ( t ) r ( t ) Reference ref Plant Command Signal r ( t ) (Flight Path Angle) + e ( t ) u ( t ) MRAC - Controller x ( t ) true True Plant y ( t ) r ( t ) (Flight Path Angle) • Demonstrate adaptive flutter suppression at two flight conditions on either side of flutter boundary without gain scheduling
Simulations – Below Flutter Boundary
• Reference model from flutter-free trim point at 115 knots, 60 lbs of fuel
Simulations – Above Flutter Boundary
• Trim point at 145 knots, 60 lbs of fuel above flutter boundary Adaptive control is able to stabilize flutter modes at different flight conditions without gain scheduling
Other Collaborations
• NASA-funded EPSCoR project with Wichita State University “Active Wing Shaping Control for Morphing Aircraft” – Wichita State University, Kansas University, and Missouri University of Science & Technology – FY15-18 performance period • Possible collaboration with Boeing Research & Technology on Integrated Adaptive Wing Technology Maturation NRA funded by AATT project