Retrofit Reconfigurable Control of an F/A-18C

1. Society of Flight Test Engineers Patuxent River, MD 16 NOV 2005 Retrofit Reconfigurable Controlof an F/A-18C Tony Page & Dean Meloney Naval Air Systems Command

2. Background • The Navy has been investing in reconfigurable control technology as part of the Flight Control Predictive Diagnostic project (ONR funded D&I program) • NAVAIR leveraged several SBIRs to expand research • One SBIR company developed a novel in-line retrofit reconfig. approach • Original plan was to flight test the method under the Phase II SBIR with support from NASA • When NASA support evaporated, decision was made to pursue flight test using D&I funds (Technology Push) • Limited flight test demonstration (4 flights)

3. Flight Control Reconfiguration Redistribute control commands to compensate for battle damage or actuator failure During a pitch maneuver for example, the ailerons and rudders can be deflected to counteract the roll and yaw coupling induced by the damaged/failed stabilator.

4. Motivation Background: numerous documented cases of loss of commercial and military aircraft and life that are attributed to major flight control system failures Problem: the full capabilities of the aircraft are not realized on production commercial or military vehicles (even those with digital flight control systems), and the pilots are often unable to effectively fly the damaged aircraft Motivation: many aircraft have intrinsic ability to maintain controlled flight and land despite flight control failures, midair collision damage, or upset conditions … Fault Tolerant Control Systems: software and/or hardware to enable fail-safe or fail adaptive operation Automatic reconfiguration to maintain controllability and recover, as closely as possible, the baseline handling qualities of the airplane

5. Status of Existing Research Status of the Field:variety of techniques and several demonstrations have shown promise of software reconfiguration to handle a large number of otherwise catastrophic upset and damage conditions • multiple significant flight demonstrations in the past 10-15 years, with several involving Boeing (Self-Repairing FCS, PCA, RESTORE) • VISTA F-16 flight tests (Self-Designing Controller, 1996) SDC Milestone: first time aircraft landed under reconfigurable control However:significant gap between the research and use of the technology … • many methods cannot be applied to current generation or legacy aircraft • hardware redundancy is common approach to fault tolerant design • V&V steps have received less attention • Federal certification authorities lack the resources to evaluate and certify novel technology Recent and Ongoing Research … Address the issues with designs that can be retrofitted into existing aircraft

6. Parallel RetrofitControl Module Sensor Data PARALLEL ARCHITECTURE modify outputs of production Controller Examples: • Direct adaptive control for civil aviation (MIT) • Control allocation methods (Boeing core effort) ^  ^ u In-line RetrofitControl Module Sensor Data IN-LINE ARCHITECTURE modify inputs to production Controller ProductionControl Law  u  Example: Current work: indirect adaptive model based control (Barron Associates and Boeing) Pilot Input Sensor Data Retrofit Reconfiguration Architectures ProductionControl Law  u  Pilot Input Sensor Data

7. Comparison of Retrofit Architectures Both Architectures Designed to be Non-Interfering • Nonzero inputs only result when performance differs from baseline Advantages of Parallel Implementation • Control of individual actuators provides more opportunities to reconfigure the aircraft Advantages of In-Line Implementation • Command limiting, structural filters, etc. remain in effect • Safety features of existing CLAW need not be duplicated or abandoned • Architecture is similar to autopilot If it isn’t broken, don’t fix it! More Powerful Should be easier to certify. Lessened V&V Requirements(if being added to an existing system)

8. How Does it Work Undamaged Airplane • Retrofit control law has model of how aircraft should respond • Available sensor data is used to identify in real-time a model of how aircraft is responding • Retrofit control law compares the two models and computes an additive command for pitch stick and roll stick in software Pilot Inputs Damaged Airplane Pilot Inputs Damaged Airplane Pilot + Retrofit Inputs Reconfiguration covers up damages to allow pilot to fly airplane with minimal manual corrections to instinctive commands …

9. Retrofit Control Law Diagram Design Concept:Adaptively computed gains are applied to feedforward, feedback, and integral error states to yield control variables (which are increments to pilot commands that recover, to the extent possible, nominal flying qualities) 3 2 Receding Horizon Control System Model Model Inputs (states, controls, airdata, etc.) 1 Ref. Model (Commanded Response) Ffq Commands Fcmd Control S Fi AW 1/s S Fpl States f 1

10. Major Components Reference Model (Prescribed Offline) • Low order equivalent system transfer functions from pilot stick to aircraft responses (i.e. pitch stick to pitch rate, roll stick to roll rate, etc.) Parameter ID System Model (Adapted Online) • State Space model with time varying parameters • Modified Sequential Least Squares algorithm – a regularizedparameter estimation method to determine system model terms Model-Based Adaptive Control (Solved Online) • Online control design procedure that operates onthe system and reference models to generate controlcommands that cause aircraft dynamics to trackreference models. • Continuous-time formulation of receding horizoncontrol for a state-space system model 1 How you want theA/C to respond 2 How the A/C isactually responding 3 How to make theA/C respond morelike what you want

11. 40 100 200 35 Dynamic Pressure (psf) 30 300 Class B Envelope 25 400 Altitude (kft) 20 15 250 KCAS Procedural Limit 10 5 0 0 0.1 0.4 0.5 0.6 0.7 0.8 0.9 0.2 0.3 Retrofit Control Law Testing Batch simulation Tens of thousands of NRTCASTLE simulation cases Pilot-in-the-loop Successful software only pilot-in-the-loop simulationtesting with Boeing andNavy Pilots Hardware-in-the-loop Extensive pilot-in-the-loop verificationof retrofit control running real-timein the FSFCC Flight Testing Two flights completed Mach Number NRT Test Point Piloted Soft. Only Sim. Test Point HILS & Flight Test Points

12. Batch Simulation Results • Completed extensive simulation testing using the Navy’s high-fidelity simulation environment (CASTLE) • Wide range of failures and damage • Turbulence • Sensor Noise • Different Aircraft Configurations • 75% of cases rated as good or excellent with regards to ability to restore nominal flying qualities • 85% of cases rated as fair or better • Majority of remaining cases did not have sufficient control power to achieve fair or better due to physical limitations

13. F/A-18 with Retrofit (for failure cases) F/A-18 with Production CAS (for failure cases) Nominal F/A-18 Pilot B Pilot A Pilot B Pilot B Pilot A Pilot A 1 2 3 4 5 6 7 8 9 10 Piloted Simulation Results Piloted Simulation Scope • Navy and Boeing pilots • Three flight conditions1: (0.7M, 20kft) 2: (0.9M, 30kft) 3: (0.6M, 30 kft) • Failures to primary aerodynamic control surfaces(stab., aileron, rudder) Bars comprise 12 to 15 HQR assessments of refueling, target tracking, bank / heading / pitch capture, etc. Cooper-Harper Handling Qualities Ratings Excellent Fair: Some Mildly Unpleasant Deficiencies Moderately Objectionable Deficiencies Loss of Control During Some Operations Major Deficiencies

14. Pilot Comments and Observations • Pilot Tracking Task (Mach 0.60, 30 kft), Left Stabilator 6 deg. Down • Close agreement between commanded & achieved pitch and roll • Data confirms pilot’s observation that “Improvement was eliminating the strong right roll-off and the roll coupling with pitch. A yaw left with pitch up, yaw right with pitch down was introduced.” • Inflight Refueling Task (Mach 0.70, 20 kft), Left Aileron 20 deg. Down • Close agreement between commanded & achieved pitch and roll • Uncommanded yaw significantly less for this flight condition and task • Data supports pilot assessment of system for this case “The elimination of the constant left stick input and the roll coupling were a sure improvement. It was hard to see a degradation in tanking resulting from any yaw coupling that may have been present. Difficult, but roughly equivalent to the baseline airplane.”

15. Retrofit Algorithm Selection • meaningful demonstration possible without pedal-augmented retrofit architecture • stick-only architecture represents appropriate tradeoff of performance and hardware implementation feasibility in the 1750A Substantial reconfiguration benefits shown in piloted simulations with rudder pedal omitted from retrofit algorithm Reconfiguration improvements of the stick and pedal retrofit control law are lessened slightly because of slower update rates in the 1750A hardware… Conclusion: use stick-only retrofit architecturefor HILS and flight testing

16. Flight Hardware • Fleet Support Flight Control Computer (FSFCC)(formerly the Production Support FCC (PSFCC)) • Standard F/A-18A-D FCC but with an additional processor card in each channel • During flight, control of the aircraft can be passed from the baseline (701E) processors to the research (1750A) processors in order to perform an experiment • Control is passed back to the standard flight control system in the event that any of the multiple safety monitors are tripped (or manually via paddle switch) FSFCC

17. Dual-Port Random Access Memory (DPRAM) PACE 1750A Research Processor dpilot dpilot d* dact Failure Sim Retrofit CLAW Streamlined Copy of F/A-18 CAS Executive Implementation of Retrofit Controller F/A-18 Fleet Support Flight Control Computer Military Spec 1553 Inputs Baseline F/A-18 Central Processing Unit (701E) Built-In Test, Executive, and Data Management Input Signal Mgmt Control Laws (V10.1) Output Signal Select & Fader Logic Actuator Signal Mgmt Surface Actuator Analog Interface Analog Inputs

18. Criteria Name Description AOA/Air Data Fail Air Data Fail or AOA Fail w/ NO WOW Disengage Request Selected ADS Switch RFCS Data Not Ready Set when RFCS Data Ready Test Fails RFCS Command not Valid Set when RFCS Command Min/Max Level Exceeded RFCS NoGo Indication Signal read from local dual port and set by 1750A. 1750A-defined logic sets no go status Actuator Failure Any 1 of 36 Failures Dual Discrete Any 1 of the 15 Dual Discrete Failures Quad Discrete Failure Any 1 of the 28 Quad Discrete Failures Quad Sensor Failure Any 2 for DISENGAGE Failures 1750A Processor Failures 1750A Watch Dog Monitor, 1750A Watch Dog Monitor Fail on Power Up, 1750A CPU Fail, 1750A PBIT PROM pair Checksum Fail, 1750A PBIT Register Fail Flag, Cross Channel Data Test Fail Dual Port Ram Invalid Dual Port RAM Ready Fail Flag, Dual Port RAM Fail Flag, or Integrator Seed Out of Limits MUX Bus Invalid MUX Bus Valid Flag Word DEL/AUTOPILOT/MECH Modes in which you cannot stay Engaged: Pitch DEL, Roll DEL, Yaw DEL, Mechanical Backup - BIT, IBIT Master Caution LEF Hydraulic Motor Fail, Flaps OFF Caution, Rudder OFF Caution, Aileron OFF Caution, Stabilator OFF Caution, DEL ON Caution Channel OFF Local X, Y, or Z OFF 701E Safety Monitoring Automatic Disengage Criteria

19. 1750A Safety Monitoring • Checks health and status of miscellaneous parameters • For example: Spin, Spin switch, heading hold • Envelope limits • Monitors p, q, r, Nz, Altitude, Airspeed, etc. • Parameters must be within predefined limits in order to engage the research processor • Research processor will automatically disengage if necessary • Limits are contained in a lookup table • Pilot selects table entry through DDI inputs

20. HILS and Flight Test Plan • Conduct flight test maneuvers and evaluate handling qualities for the following scenarios: • Retrofit control inactive, no failures(provides nominal performance baseline) • Retrofit control active, no failures(demonstrates non-interference) • Retrofit control inactive, with failures(provides degraded performance baseline) • Retrofit control active, with failures(demonstrates benefit of reconfiguration) • Failures under consideration • Right aileron stuck at given position (± 30° offset) • Right stabilator stuck at given position (± 6° offset)

21. dstick / max(dstick) q / max (q) Time (sec) HILS and Flight Test Plan (cont’d) • Flight test maneuvers • Stick doublets • Pitch and bank angle captures • “Guns” tracking (with chase as target) • Aircraft configuration • F/A-18C • Clean with exceptionof center-line tank • CR and PA

22. Cooper-Harper Handling Qualities Ratings Fair: Some Mildly Unpleasant Deficiencies Moderately Objectionable Deficiencies Loss of Control During Some Operations Excellent Major Deficiencies 1 2 3 4 5 6 7 8 9 10 Pilot: “TOD” (Maj. Matt Doyle) HILS Results: 30° Aileron Failure (UA) Average HQR = 1.5 Guns Tracking HQR = 2.0 Bank-to-Bank Rolls HQR = 1.0 Pitch Attitude Capture HQR = 1.5 Retrofit – Smooth Mnvr. / Coarse Tracking V10.1 CAS – Smooth Mnvr. / Coarse Tracking Legend Retrofit – Aggressive Mnvr. / Fine Tracking V10.1 CAS – Aggressive Mnvr. / Fine Tracking

23. Flight Test: 30° Aileron Failure (v10.1)

24. Flight Test: 30° Aileron Failure (Retrofit)

25. Cooper-Harper Handling Qualities Ratings Fair: Some Mildly Unpleasant Deficiencies Moderately Objectionable Deficiencies Loss of Control During Some Operations Excellent Major Deficiencies 1 2 3 4 5 6 7 8 9 10 Pilot: “TOD” (Maj. Matt Doyle) Flight Results: 30° Aileron Failure (UA) Average HQR = 1.6 Guns Tracking*(Maneuvering) HQR = 1.0 Guns Tracking*(Level Turn) HQR = 2.0 Bank-to-Bank Rolls HQR = 1.0 Pitch Attitude Capture HQR = 2.5 Retrofit – Smooth Mnvr. / Coarse Tracking V10.1 CAS – Smooth Mnvr. / Coarse Tracking Legend Retrofit – Aggressive Mnvr. / Fine Tracking V10.1 CAS – Aggressive Mnvr. / Fine Tracking

26. Mach Number NRT Piloted Soft. Only Sim. HILS & Flight Test 40 100 200 35 Dynamic Pressure (psf) 30 300 Class B Envelope 25 400 Altitude (kft) 20 15 250 KCAS Procedural Limit 10 5 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 R&D Summary • Tens of thousands of NRT CASTLE simulation cases • Successful piloted simulations with Boeing & Navy pilots • Implementation in US Navy F/A-18 FSFCC • Successful HILS piloted testing • Half way through flight test program F/A-18 flight testing at Patuxent River NAS …

27. Back-up Slides

28. Open Literature Publications Barron Associates, Inc. Ward, D. and Monaco, J., "System Identification for Retrofit Reconfigurable Control of an F/A-18," AIAA Journal of Aircraft (to be published). Monaco, J., Ward, D., and Bateman, A., "A Retrofit Architecture for Model-Based Adaptive Flight Control," AIAA Paper No. 2004-6281, in Proc.of AIAA Intelligent Systems Conference, Sep. 2004. Boeing and NAVAIR Black, S., et. al., "Reconfigurable Control and Fault Identification System," 2004 IEEE Aerospace Conference. March 6-13, 2004, Big Sky, MT.

29. NAVAIR Program Background • The Navy has been investing in reconfigurable control technology as part of the Flight Control Predictive Diagnostic (FCPD) project • FCPD Objective: To develop & demonstrate damage & failure diagnostics/prognostics approaches for reconfigurable control, condition-based maintenance, and improved situational awareness Health, Faults, Anomaly Aircraft Level Component Health Faults, Health Observable at A/C System Level Damage ID Component Status Ability to perform in-flight tests without disrupting flight Health Status Fusion Flight Control Reconfiguration System and Component Health Faults, Health Observable at Component Level Inform of remaining capability Maintenance Support: • Prognostics Pilot or Autonomous System Action: • Reconfiguration Compensates for Damage and Failures

30. FSFCC Hardware is Flight Proven • Developed jointly by NAVAIR and NASA • Derivative of NASA HARV configuration • Compatible with any F/A-18A-D • Requires flight test jumpers installed on MCs • Requires DAF • Originally Flight tested at NASA Dryden and at Patuxent River in 1998 (FSFCC V1.1 Software) • 3 flights at NASA Dryden • 11 flights at Patuxent River • All test objectives met

31. Pilot Interface 1 2 DDI [A] to completesequence and arm FSFCC DDI [B], [C], [D] combinations to define test 3 4 For Example DCCBBB = Table 22 Row 0 (Fail R Stab to 0) CCBCB = Table 4 Row 3 (Nz Upper Limit Table Entry 1) NWS button to engage FSFCC ADS paddle to disengage FSFCC

32. Major Components Reference Model (Prescribed Offline) A model that encodes the desired aircraft responses to pilot inputs as a function of operating condition, etc. • Low order equivalent system transfer functions from pilot stick to aircraft responses (i.e. pitch stick to pitch rate, roll stick to roll rate, etc.) • Model parameters computed from high-fidelity simulation data of nominal (unimpaired) aircraft • Model parameters at a given operating condition are functions of input magnitude (see figure) • Reference model integrated online (80 Hz update in the 1750A FSFCC) Parameter ID System Model (Adapted Online) A model that encodes the dynamical responses of the aircraft as it maneuvers through the flight envelope. • State Space model with time varying parameters • Modified Sequential Least Squares algorithm – a regularized parameter estimation method to determine system model terms • MSLS update of system model done online (5 Hz update in the 1750A FSFCC) 1 Example: Transfer Function Gain, Roll Axis Ref. Model 2

33. Major Components (cont’d) Model-Based Adaptive Control (Solved Online) Online control design procedure that operates on the system and reference models to generate control commands that cause aircraft dynamics to track reference models. • Continuous-time formulation of receding horizon control for a state-space system model • “Optimal” solution via differential Riccati equations replaced with approximate solution to integrate control law gains directly • 30 percent less memory, 25 percent faster computation • Closed loop simulation performance comparable for set of test cases considered • Control gain differential equations solved online (10 Hz update in 1750A FSFCC) • Most recent control gains applied at basic frame rate (80 Hz in 1750A FSFCC) 3

34. Control Law Cost Function RHO is a solution to the finite horizon optimization problem that minimizes symmetric positive semidefinite weighting matrix that assigns importance to predicted tracking error symmetric positive semidefinite weighting matrix that assigns importance to integrated tracking error symmetric positive definite weighting matrix that penalizes control effort