ACGSC Meeting 99, Boulder Wed, Feb 28, 2007 Barron Associates, Inc. Selected Current Research SAE International Aerospace Control & Guidance Systems Committee Boulder, Co Feb 28, 2007 David G. Ward (434) 973-1215 ward@barron-associates.com -1-
ACGSC Meeting 99, Boulder Wed, Feb 28, 2007 Adaptive Control of Morphing Aircraft Shape K FQ K FQ Control c c x PL x PL x FQ x FQ e e B FQ B FQ 1/s 1/s C FQ C FQ - - K I /s K I /s B PL B PL 1/s 1/s C PL C PL Objective Adaptive Control Flight A FQ A FQ A PL A PL Control 35 K PL K PL x PL =[ q] T x PL =[ q] T 30 25 Morph and maneuver Pitch Attitude (deg.) Goal: Stable flight control with limited model initiated at 15 sec. 20 knowledge during wing-shape morphing 15 Commanded Response Response ( = 1/3 sec.) 10 Conventional Control: c c e e Response ( = 3 sec.) - - K P + K I /s K P + K I /s P(s) P(s) Response ( = 30 sec.) 5 Response ( = sec.) 25 0 20 -5 0 10 20 30 40 50 60 Pitch Attitude (deg.) Time (sec.) 15 *in s t a b ilit y o c c u rs fo r > 0 . 1 7 Response ( = 6.7 sec.) Result: Consistent stable response Response ( = 10 sec.) 10 Response ( = sec.) AF SBIR AF SBIR Ph Phase II 5 � With Morph and maneuver = 0 0 initiated at 0 sec. = 0 . 1 NextGen / Northrop Grumman / VA Tech = 0 . 1 5 � Bryan Cannon, COTR -5 0 2 4 6 8 1 0 1 2 1 4 1 6 1 8 2 0 0 2 4 6 8 10 12 14 16 18 20 Dem Demonstr trati tion Goal Time (sec.) Result: Inconsistent response and instability � Real-time wind-tunnel demonstration of stable for faster morph times ( >6 sec.) morphing control using N-MAS wing -2-
ACGSC Meeting 99, Boulder UAV Upset Recovery Control Systems Wed, Feb 28, 2007 Collaboration w NASA LaRC (Drs. Christine and Celeste Belcastro) COTR: Mr. Jim Busey, NAVAIR High-Fidelity Simulation Develop a general-purpose NATOPS, NATOPS, Established Established automated-recovery Recovery Recovery Procedures, Etc. Procedures, Etc. system approach that Manned Manned � learns appropriate recovery Aircraft Aircraft Flight Data, Flight Data, strategies Piloted Piloted � adopts/encodes best-practices Simulations Simulations from the manned aircraft community CUPR � avoids out-of-control conditions to the extent possible � takes advantage of innovative EAGLE EY E actuation concepts EAGLE EYE -3-
ACGSC Meeting 99, Boulder Innovative Methods for Optimally Mixing a Diverse Wed, Feb 28, 2007 Suite of Control Effectors for Marine Vehicles Onboard Models Heading Overshoot Depth Overshoot 30 20 Cmnds Multi-input Multi- Control 18 output Control Law Allocation 25 Phase II Acceptance Bound Phase II Acceptance Bound 16 14 Ph Phase II II Pl Plan 20 12 Form rmalize inner-loop contr trol design 15 10 meth thodology to be applicable to any vehicle wi with th 8 10 6 minimal re reconfi figurati tion and tuning - fe feedback 4 5 lineari rizati tion and backste tepping 2 0 0 Dev Develop model based tuning approaches -0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Dev Develop meth thods to esta tablish sta tability ty, robustness and perf ro rform rmance characteri risti tics of inner-loop approaches Dev Develop state te esti timati tion appro roaches Dev Develop oute ter-loop guidance design meth thodology that can be applied to a vari riety ty of vehicle platf tforms Dev Develop path th planning algori rith thm Ap Apply design meth thodology to to multiple vehicle models and evaluate te perf rform rmance - - - Phase I Sponsor: - - Dr. Edward Ammeen Head, Maneuvering and Control Division M Naval Surface Warfare Center, Carderock Tel: (301) 227-5907 -4-
ACGSC Meeting 99, Boulder NASA SBIR/STTR Technologies Wed, Feb 28, 2007 Damage Adaptation using Integrated Structural, Propulsion, and Aerodynamic Control PI: D. Ward, Barron Associates, Charlottesville, VA Topic A1.02 Integrated Resilient Aircraft Control -- Submittal No. A1.02-9516 Identification and Significance of Innovation Structural Structural Structural Structural Structural Structural Structural Structural Structural Structural Structural Structural Health Health Health Health Health Health Health Health Health Health Health Health Monitoring Monitoring Monitoring Compensate for Simultaneous Monitoring Monitoring Monitoring Monitoring Monitoring Monitoring Compensate for Simultaneous Monitoring Monitoring Monitoring Effector, Airframe, and Propulsion Damage Effector, Airframe, and Propulsion Damage Aerodynamic Aerodynamic Aerodynamic Aerodynamic Aerodynamic Aerodynamic Aerodynamic Aerodynamic Aerodynamic Aerodynamic Aerodynamic Aerodynamic System ID System ID System ID System ID System ID System ID � Built on flight-test-proven reconfigurable control System ID System ID System ID System ID System ID System ID algorithms � Compute feasible control using aerodynamic and Engine Engine Engine Engine Engine Engine Engine Engine Engine Engine Engine Engine Diagnostics Diagnostics Diagnostics propulsive “effectors” Diagnostics Diagnostics Diagnostics Diagnostics Diagnostics Diagnostics Diagnostics Diagnostics Diagnostics � Compute safe operating envelope in real-time Integrated Integrated Integrated Integrated using real-time structural health monitoring (1) Yoke, Pedal, and Thrust Commands (1) Yoke, Pedal, and Thrust Commands Integrated Integrated Integrated Integrated (1) Yoke, Pedal, and Thrust Commands (1) Yoke, Pedal, and Thrust Commands Damage- Damage- Achievable, Decoupled, Safe… Achievable, Decoupled, Safe… Damage- Damage- Damage- Damage- � No excessive loads on damaged components Achievable, Decoupled, Safe… Achievable, Decoupled, Safe… Damage- Damage- Adaptive Adaptive Adaptive Adaptive Adaptive Adaptive � No excitation of new structural modes (2) Landing Trajectory (2) Landing Trajectory Adaptive Adaptive Control Control (2) Landing Trajectory (2) Landing Trajectory Control Control Achievable, Safe… Achievable, Safe… Control Control � Path-plan for safe landing Achievable, Safe… Achievable, Safe… Control Control � No unachievable trajectories or autopilot commands � No violation of structural limitations � Can be implemented using V&V’able architectures NASA and Non-NASA Applications Civil Aviation, Military Aviation, Space, Civil Aviation, Military Aviation, Space, Technical Objectives and Work Plan Life-Extending Control, … Life-Extending Control, … Simulation Demonstration of Integrated Simulation Demonstration of Integrated Damage Adaptive Control System � Improved aircraft safety for civilian aviation Damage Adaptive Control System � Improved autonomous operations for space Work Tasks exploration in environments with massive � Define demonstration problem (GTM / AirSTAR?) uncertainties � Integrate representative health-monitoring system � Improved autonomous operations for military � Develop integrated damage-adaptive controller vehicles (air, ground, surface, underwater, …) � Integrate autopilot and path-planning approaches � Life-extending control � Simulation demonstration � Use during normal conditions to reduce wear/fatigue on key structural components Contact: 434-973-1215 ward@barron-associates.com NON-PROPRIETARY DATA -5-
ACGSC Meeting 99, Boulder Wed, Feb 28, 2007 IAG&C Through RLV Flight Envelope Air Force’s Fully Reusable Access to Space In Involved in all fli light phase ses Technology (FAST) Program Curre rrent fo focus is on FA FAST ST De-Orbit Burn Orbit Insertion 2 nd stage 1 st stage 2 nd Stage Entry Burn Altitude Mated vehicle 2 nd Stage Coast 1 st Stage 2 nd Stage Separation Abort/Recovery 1 st Stage Lift-Off TAEM Recovery Approach/Landing Time -6-
ACGSC Meeting 99, Boulder Wed, Feb 28, 2007 IAG&C for RLVs during Re-entry Go Goals/O s/Obje ject ctive ves � Adapt for effector failures � Integrate with existing RCS systems � Manage heating constraints, etc. AFRL BAA w/ Boeing (Anhtuan Ngo, COTR) -7-
ACGSC Meeting 99, Boulder Wed, Feb 28, 2007 Architecture Archite tect cture for re-entry tr trajecto ctory command generation Adaptive Trajectory Adaptive Trajectory Reconfigurable Reconfigurable Guidance Command Command Guidance Control System Control System Generation System Generation System q cmd mag + ref Lateral Traj. Longitudinal Lateral Traj. 3-DOF Plant Longitudinal 3-DOF Plant Traj. Algorithm Algorithm Model Traj. Algorithm Algorithm Model Cmd. - Traj. q Lift, States Drag, … , Onboard Current estimates of Dynamic Parameter Pressure lift, drag coefficients Estimation Profile Reshaping -8-
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