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Air Vehicles Directorate Activities

Air Vehicles Directorate Activities Aerospace Control and Guidance Systems Committee Lake Tahoe, NV March 1 – 3, 2006. David Doman david.doman@wpafb.af.mil Control Science Center of Excellence Air Force Research Laboratory, WPAFB. Control Science Center of Excellence. Research Areas

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Air Vehicles Directorate Activities

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  1. Air Vehicles Directorate Activities Aerospace Control and Guidance Systems CommitteeLake Tahoe, NVMarch 1 – 3, 2006 David Doman david.doman@wpafb.af.mil Control Science Center of Excellence Air Force Research Laboratory, WPAFB

  2. Control Science Center of Excellence • Research Areas • Cooperative control of UAVs • Fault tolerant autonomous space access and prompt global strike • Feedback flow control • Personnel • Civil servants – 11 • Military – 2 enroute • Contractor – 3 • Increase by 2/3 in summer

  3. Agile Combat Support Agile Combat Support Force Application Command & Control Long Range Strike Prompt Global Strike Persistent Strike Cooperative Airspace Ops Strike Agile Combat Support Agile Combat Support ISR Mobility Persistent ISR Operationally Responsive Space Access & Reconnaissance Force Projection Multi-Role All-Environment Mobility Surveillance Contributing to VA Capability Focus Areas CAV Precision GNC Long-term HSV Vision Hingeless maneuvering Cooperation with autonomy Shear layer control Reliability Safety Responsiveness Higher L/D

  4. Cooperative Operations in UrbaN TERrain (COUNTER) MAVs Critical Information to Warfighter • Provide Situational Awareness for Urban Operations • Positive Identification and Verification of Target in Cluttered Urban Environments • Is Something/Someone Important There? • Where? • What/Who? • Micro Aerial Vehicles (MAVs) • Details/Positive ID • Fly Inside City for Positive Target ID • Look Angles for Obscured Targets • Small UAVs • Big Picture • Wide Field of View but Limited View Angles • Relay and Processing of MAV Data

  5. Object Allocation Algorithm – 6.1 Research • Problem: minimize the maximum tour length for all vehicles • Constraints: • Large number of targets (20) • Real time implementation • Flyable trajectories • Solution • Branch and Bound algorithm • Decouple task assignment from trajectory optimization • Traveling Salesman Problem solver • Appeal • fast feasible solution • monotonic improvement of solution • Flight Test April 06 6.1 research providing critical algorithms for a multi-directorate 6.2 demo program

  6. Temp. Air-breathing Hypersonic Vehicle Modeling and Control • Problem: model and control a highly coupled airframe/propulsion system with aerothermoelastic interactions. • Challenges: • Complex interactions between aerodynamics, propulsion, structures, and thermal protection system • Aerothermoelastic phenomena necessitates multidisciplinary modeling • Vehicle closed-loop response bandwidth limited • Approach: • First principles modeling approach • Include thermal effects on structural dynamics • Investigate configuration modifications to improve controllability • Status: • Increasing model fidelity include unsteady heat transfer for a legacy TPS • Identified canard-elevon configuration that significantly improves flight path controllability “Aerothermoelasticity” Mode Shapes Hot Cold Freq. Canard-Elevon Interconnect Interconnect Effect on RHP Zero

  7. Fault Tolerant Responsive Space Access and Prompt Global Strike • IAG&C completed X-37 HILS testing this year at Boeing ASIL Facility • Follow-on to 2003 TIFS/X-40 AL Demo • AFRL / Barron Associates / Boeing team • 3D TAEM/AL trajectory reshaping demonstrated • Reconfigurable inner-loop control • Other flight phases: boost, post-boost and reentry to follow • Prompt Global Strike project • Ablation effect modeling and simulation • Adaptive PN terminal guidance with limits • Severe control power limitations • Tight impact requirements

  8. 7 Velocity m/s 8 4 5 6 Aerodynamic Flow Control (OSU/CCCS) Objective:Improve robustness of aerodynamic flow control for cavity flows Technical Challenges: • Order reduction of Navier-Stokes equations in a way that is amenable to control law design • Controller design for highly nonlinear systems Application: Reduce aero-acoustic loading on weapons bay structures • Progress: • Developed and implemented linear quadratic control based on reduced-order models obtained using experimental data and three numerical techniques. • Demonstrated advantages of closed-loop control (via simple linear controllers) over open-loop control (forcing at optimal frequency and amplitude)

  9. Strong Collaboration: • Joint Research & Publications Industry visits • Invited sessions Weekly tech discussions • Seminars In-depth 6-month reviews Control Science Collaborative Center • Team:Ohio State University (lead), UD, UC, and AFIT • Manpower:7 faculty, 3 post docs, 12 grad students • Established in Oct 2001 • $1Mper year shared equally by VA and AFOSR • Cost share:$700K from State of OH, $1,055K from OSU, UC & UD • Synergies and leveraging:$6M from NASA, NSF, NIST, DARPA • Formal annual reviews: 100+ attendees from DoD & industry • ExecutiveBoard consists of government, industry, academia CCCS considered a “Model Center”

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