PI: Asst. Prof. Joseph F. Horn Tel: (814) Graduate Student: Nilesh Sahani Project PS 5.1 Carefree Maneuvering Control Laws for Rotorcraft 2005 RCOE Program Review May 3, 2005

Background / Problem Statement  Rotorcraft are constrained by multiple flight envelope limits. It is a major contributor to pilot workload.  Carefree Maneuvering (CFM) systems allow us to avoid using conservative operational envelopes. Pilots can use maximum performance and maneuverability without sacrificing safety, reliability, handling qualities  Can be achieved through cueing systems or AFCS Carefree Maneuvering (CFM) Control System Using Tactile Cueing Technical Barriers  Robust and efficient algorithms to predict onset of limits and control constraints to avoid the limits  Develop systems that do not take away a pilot’s option to exceed a limit and do not annoy the pilot  Avoid adding costly sensors or systems  Need comprehensive systems that handle multiple limits and multiple control axes  Integration of envelope cueing with envelope limiting AFCS  Quantify the payoffs of CFM in terms of handling qualities, safety, reliability, maintainability  Exploit potential use of CFM technology on UAV’s

Task Objectives:  Develop limit detection and avoidance algorithms for peak responses and transient limits  Develop an integrated CFM control architecture that features cueing and limiting in the AFCS  Develop practical systems, demonstrate technologies in piloted simulation / flight test  Apply CFM technology to UAV’s Approaches:  Develop improved transient limit prediction algorithm and constraint calculation methods  Cooperation with industry / academic partners (Sikorsky / Georgia Tech), in order to demonstrate systems in piloted simulations and flight tests  Focus on comprehensive collective axis cueing and hub moment limiting systems  Extend technologies to integrate with advanced AFCS designs / UAV flight controls Expected Results:  Develop limit avoidance methods for advanced AFCS designs / UAV flight controls  Evaluate integration of envelope protection system with UAV flight controls  An assessment of the requirements for effective carefree maneuvering control systems  Some measure of the potential payoffs of carefree maneuvering technology

Outline of Technical Presentation  Piloted Rotorcraft / Cueing Systems  Review - Longitudinal hub moment limit avoidance algorithm  Pilot cueing techniques  Results  Comparison of different techniques  UAVs / Future Rotorcraft  Overview of control architecture – Inner loop / outer loop structure  Problem with implementing envelope protection system within the feedback loop  Continuous torque limit protection for UAVs  Generating constraints on outer loop command  Results

Limit Avoidance Algorithm - Transient Limits Find dynamic trim values Offline trained neural networks Stick constraint calculation Scan through time

Background – Swoop Maneuver Desired Performance Adequate Performance Integrated Hub Moment Limit Exceedance Factor (IHMLF)  Time integral of hub moment above limit  Sum of all green pained areas

Swoop Maneuver Results Slight increase in maneuver time  Does not inordinately restrict agility of the aircraft Reduction in integrated hub moment violations  less fatigue wear Reduction in absolute peak hub moment  reduced risk of catastrophic failure Pilot comments: softstop cue for hub moment objectionable during very aggressive maneuvers

Command Shaping for Limit Protection Pure automatic limit protection  Does not allow pilot to override limit  Useful for evaluating the effectiveness of the prediction algorithm only  Gives a standard for comparing other cueing techniques

Command Shaping for Limit Protection Deadband  Allows pilot to override the limit  Can be implemented using stick shakers  Provides easier upgrade than softstop

Advanced Cueing Methods (proposed by our colleagues at Georgia Tech) Dynamic Overshoot Compensation  Sidestick momentum can inadvertently climb over a softstop cue  Can result in transient limit violation  Technique: No change to softstop - Fleeting command restraint Frequency Distribution  Technique: Low frequency component for pilot cueing - High frequency component for autonomous protection

Performance Evaluation  Limit Protection Approaches  Pure Autonomous  Deadband  Dynamic Overshoot Compensation  Frequency Content Distribution  Same underlying longitudinal hub moment limit avoidance algorithm (developed by PSU)  Summary  Softstop cueing provided better results compared to stick shakers  Overshoot/ Freq. Distribution  Smaller maneuver time  Fewer limit violations  better pilot-in-the-loop performance  Best results using frequency distribution  “Steadier” softstop of Freq. Dist. was noticed and preferred  Constraint calculation (PSU) + Pilot cueing (GT) = Smallest maneuver time + Fewer limit violations  Agility + Component Life

Conclusions from Piloted Simulation  Algorithm was reasonably effective in predicting the constraints  Neural Network - Predicts critical value of the future response over some time interval  Sensitivity for constraint calculation  Constraints moved too quickly for the pilot to react efficiently to a pure soft stop cue  Frequency distribution of constraints provided best results  Low frequency component – softstop cue  High frequency component – Autonomous protection  Pilot was able to interact with the softstop much more efficiently  Maneuvers consistently resulted in smaller maneuver time and fewer limit violations  Satisfactory pilot in the loop performance – no major pilot objections

Limit Avoidance for UAVs / Future Rotorcraft  Future rotorcraft / UAV are likely to feature model following / inversion controllers  Structural limit protection desirable  To save weight on future designs (particularly on large aircraft)  To protect highly agile vehicles with high bandwidth flight controls  Achieve limit protection with constraints in desired response (not in feedback loop) Aircraft Sensors Limit Parameter to Command Dynamics Limit Prediction Tracking Controller Pilot Pilot Control Velocity / Angle Commands Desired Response ACAH / RCAH Active Control Stick Constraints on Desired Response Limit Avoidance Trajectory Tracking UAV

Saturation Outside Feedback Path Saturation Inside Feedback Path Problems with Constraints in Feedback Loop

Inner Loop / Outer Loop Controller  Controller implemented for GENHEL  Outer loop – trajectory commands  Inner loop – velocity / angle commands – for aggressive maneuvers  Maneuver switch for command switching  Challenges:  Ensure continuity of constraints with command switching  Closed loop stability due to saturation constraints in feedback path PI Error Dynamics From Sensors To Command Filter Maneuver Switch Inner Loop Commands Outer Loop Commands Aircraft Inversion Controller PID Error Dynamics Command Filter ANN Inner Loop Commands acc. command Notch Filter Pos. / Vel. command Inner Loop Sensors

Continuous Torque Limit  Dynamic Trim algorithm  Offline trained neural network for future response prediction  Sensitivity to command input for constraint calculation  Constraint on descent velocity corresponding to transmission torque limit  Constraint on Inner loop command Aircraft Command Filter Torque Prediction (Neural Net) Measured Torque Torque Limit Envelope Constraint Calculation

Cont. Torque Limit Evaluation – Inner Loop  Envelope protection off  Torque exceeds the limit  Envelope protection on  Steady state torque stays close to the limit  Constraint on descent velocity (Inner loop) command  Saturation limit inside feedback loop when using altitude (outer loop) commands

Moving Constraints out of Feedback Loop + - Move outside feedback loop  Example: P/PI Controllers  P: {A=0 B=0 C=0 D=K p }PI: {A=0 B=1 C=K i D=K p }  Heave Axis:  Inner Loop Command – Descent Velocity  Outer Loop Command – Altitude (Using Proportional controller)  Why:  Affects closed loop stability  Pilot cueing of command input

Cont. Torque Limit Evaluation – Outer Loop

Flight Simulation Future Upgrades Honeywell 2-Axis Active Sticks Donated by Boeing - Philadelphia Bell 206 Simulation Cockpit Donated by Bell-Textron

Accomplishments 2004 Accomplishments  Continued collaboration with Georgia Tech. – Evaluated different pilot cueing techniques  Demonstrated in piloted simulation that accurate prediction algorithm and appropriate pilot cueing techniques do result in smaller maneuver time and reduced limit violations  Integrated hub moment limiting constraints with adaptive model following controller  Integrated continuous torque limiting algorithm with inner loop /outer loop type controller – useful for autonomous UAVs  Continued to produce publications Planned 2005 Accomplishments  Integrate Active Control Stick with simulator at PSU  Implement CFM systems on real-time simulator at PSU  Continue development of CFM integrated with adaptive model following controller for UAV’s or manned aircraft  Further assessment of CFM impact on reduction of loads and handling qualities

Schedule and Milestones Tasks Hub moment limit detection and avoidance system Develop comprehensive collective axis cueing system Demonstrate in piloted simulation at Sikorsky Simplify algorithms for practical flight system Develop integrated CFM cueing and control laws Piloted simulation / HQ evaluation of integrated CFM Integrate with adaptive control Quantitative assessment of benefits of CFM Develop CFM for UAV’s Sahani MS Degree Sahani PhD Degree 2003 Completed Short Term Long Term

Technology Transfer Activities: Leveraging or Attracting Other Resources or Programs: Recommendations at the 2004 Review: Presentation too long, needs better focus Talk directly to PIs from HACT project Review team questioned usefulness of structural load limiting Resolve export control issue when dealing with DLR Continued collaboration with Georgia Tech RCOE in simulator work, have discussed potential transfer to their UAV work Publications - AIAA Journal of CIC, AIAA Journal of GCD (accepted), AHS Journal (under review), AIAA GNC Conference, AHS Forum Briefings to Boeing, Sikorsky, Lockheed Collaboration with Prof. Asok Ray on ARO MURI. Task “Damage Mitigating Control for Rotorcraft”. Incorporating CFM technology into that work. Active control sticks donated by Boeing Actions Taken: Addressed in presentation development Had discussions and exchange of information with P. Einthoven at Boeing Addressed in following slide No longer planning collaboration with DLR

Relevance of Structural Load Limiting Work  Last review the question was posed “Who Cares?”  RAH-66  Hub moment limiting was implemented in RAH-66 by limiting pitch acceleration commands. Seemed to work adequately but …  Constraints not as accurate our system  Constraints were inside feedback loop for outer loop controls – should avoid this if possible.  NASA Heavy Lift Rotorcraft Systems  Effort to reduce weight  Automatic Load Limiting / Hub Moment Control identified as a desirable technology for heavy lift rotorcraft  Weight savings could be achieved using better loads estimates to remove conservatism – or actively limit loads to remove conservatism  HACT Program  Discussion with P. Einthoven at Boeing Philadelphia. He identified the need to more rigorously study closed-loop stability.

Overview of Accomplishments Comprehensive Collective Axis Limit Avoidance  Includes transmission torque limits, engine torque limits, rotor RPM limits, OEI and autorotation limits  Collaborated with Sikorsky – Evaluated in piloted simulation Publications  Conference: 6 Journal: 2 published + 1 accepted + 2 under review Longitudinal Hub Moment Limit Avoidance  Developed new algorithm that provided accurate constraints over entire flight envelope  Evaluated in piloted simulations at Georgia Tech.  Evaluated different pilot cueing technique  Demonstrated in pilot sim. : CFM results in smaller maneuver time and reduced limit violations Integration of CFM with Model Following Controller (MFC)  Integrated long. hub moment limit protection with MFC  Integrated torque limiting with inner loop/ outer loop controller architecture

Future Path Additional Basic Research Transition to Applications / Applied Research Potential for more research on basic stability issues of load limiting and bio-mechanical issues of tactile cueing. Investigate use for vibratory loads limiting – need comprehensive analysis code (RCAS) Incorporate CFM technologies within a damage mitigating control / life extending control architecture Near-term potential for application to UAV systems Georgia Tech implementing their controller on Boeing Maverick UAV (uses R-22 airframe) – potential application for mast bumping / torque limiting Long term application on heavy lift rotorcraft – use CFM methods to save weight. There needs to be further study of certification issues for active control sticks and tactile cueing systems.