Aircraft Turbine Engine Control Research at NASA Glenn Research Center

Dr. Sanjay Garg Chief, Intelligent Control and Autonomy Branch Ph: (216) 433-2685 FAX: (216) 433-8990 email: [email protected] http://www.grc.nasa.gov/WWW/cdtb

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Outline – The Engine Control Problem • Safety and Operational Limits • State-of-the-Art Engine Control Logic Architecture – Historical Glenn Research Center Contributions • Early Stages of Turbine Engine Control (1945-1960s) • Maturation of Turbine Engine Control (1970-1990) – Advanced Engine Control Research • Recent Significant Accomplishments (1990- 2004) • Current Research (2004 onwards) – Conclusion

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Basic Engine Control Concept • Objective: Provide smooth, stable, and stall free operation of the engine via single input (PLA) with no throttle restrictions • Reliable and predictable throttle movement to thrust response

• Issues: • Thrust cannot be measured • Changes in ambient condition and aircraft maneuvers cause distortion into the fan/compressor • Harsh operating environment – high temperatures and large vibrations • Safe operation – avoid stall, combustor blow out etc. • Need to provide long operating life – 20,000 hours • Engine components degrade with usage – need to have reliable performance throughout the operating life

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Basic Engine Control Concept

• Since Thrust (T) cannot be measured, use Fuel Flow WF to Control shaft speed N (or other measured variable that correlates with Thrust • T = F(N) Pump fuel flow from Accessories fuel tank Control Sensor Throttle

Pilot’s Compute Meter the Inject fuel Measure power desired fuel computed flow into produced request flow fuel flow combustor power

Valve / Fuel nozzle Actuator Yes Determine No Power operating desired? condition

Control Logic

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Environment within a gas turbine

2000+ºC Aerodynamic 20000+ hours Flame temperature Buffeting Cooling air Between service 120 dB/Hz to 10kHz - 40ºC ambient at 650+ºC

40+ Bar Gas pressures

Foreign objects Birds, Ice, stones Air mass flow ~2 tonne/sec 8mm+ Shaft movement

50 000g centrifugal 2.8m acceleration 1100+ºC Diameter >100g casing vibration Metal temperatures to beyond 20kHz 10 000rpm 0.75m diameter

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Operational Limits

• Structural Limits: • Maximum Fan and Core Speeds – N1, N2 • Maximum Turbine Blade Temperature • Safety Limits: • Adequate Stall Margin – Compressor and Fan • Lean Burner Blowout – minimum fuel • Operational Limit: • Maximum Turbine Inlet Temperature – long life

Wf Ps surge 30 over-temp

over over

-speed - pressure Operational Limits Mapped into Acceleration Limits on allowable fuel flow (ratio of fuel flow to combustor pressure) as a Operating line function of Corrected Fan Speed

Deceleration - Referred to as Accel/Decel Schedule blowout

R N2 Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Fuel flow rate (Wf) or fuel ratio Historical Engine Control unit (Wf/P3) Safe operating region

Max. flow limit Droop slope Proportional control gain or droop slope Required fuel flow @ steady state

Min. flow limit Idle Max. power power GE I-A (1942) Engine shaft speed • Fuel flow is the only controlled variable. - Hydro-mechanical governor. - Minimum-flow stop to prevent flame-out. - Maximum-flow schedule to prevent over-temperature

• Stall protection implemented by pilot following cue cards for throttle movement limitations Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Typical Current Engine Control • Allows pilot to have full throttle movement throughout the flight envelope - There are many controlled variables – we will focus on fuel flow

• Engine control logic is developed using an engine model to provide guaranteed performance (minimum thrust for a throttle setting) throughout the life of the engine - FAA regulations provide an allowable maximum rise time and maximum settling time for thrust from idle to max throttle command Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Burst-Chop Example – Inputs/Outputs

100 2500 n 20 Nf limit 2000 deg) demand 15 50

Nf (rpm) 1500

TRA (deg) 10 VSV pos. ( VSV pos. 0 1000 5 0 10 20 0 10 20 0 10 20

4 x 10 2.5 60 n 50 open) 2 Phi max 40 1.5 40 Phi min

20 Wf (pph) 1 30 p 0.5 Wf/Ps30 (pph/psi) VBV pos. (% (% VBV pos. 0 20 0 10 20 0 10 20 0 10 20

9500 n 500 n 9000 n 2000 T48 limit Ps30 hi limit Nc limit 400 R) 8500 q 300 1500 T48 ( T48 Nc (rpm) 8000 200 Ps30 (psia) Ps30 low limit 7500 100 p 1000 0 10 20 0 10 20 0 10 20 Time (s) Time (s) Time (s)

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Early Stages of Turbine Engine Control (1945-1960s) • Time-Domain Closed-loop Engine Analysis • Corrected Parameters for Model Simplification • Simplified Dynamic Model of Engine Response • Real-time Engine Dynamic Modeling Using Computers

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Time-Domain Closed-Loop Engine Analysis

1948: GE tests the first afterburning turbojet in the world – J47: • Hydro-mechanical fuel control for main fuel flow and electronic (vacuum tube) fuel control for afterburner • Limit cycle observed in altitude testing at GRC – noise from speed sensor feeding into the “high gain” of the speed governor • GE and NASA engineers worked together to solve the problem – performed time-domain studies to identify the problem and reduce the control gain at altitude

This established the strong industry/government partnership in engine controls development which continues to this day

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Corrected Parameters for Model Simplification

• Engine steady-state performance obtained through cycle calculations using slide rule / desk calculators – Performance calculations at each operating point took several hours • NASA engineers developed the concept of “Corrected Parameters” – performance parameters corrected to non- dimensionless temperature and pressure w.r.t. sea level static conditions – Considerably reduced the amount of time to develop engine steady-state performance model – from months to a few weeks, and also reduced the amount of experimental testing to be done Corrected Parameters concept is being used to this day for engine simulation and analysis Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Simplified Dynamic Model of Engine Response • Dynamic behavior of single-shaft turbojet first studied at NACA Lewis Laboratory in 1948

The study showed that the transfer function from fuel flow to engine speed can be represented by a first order lag linear system with a time constant which is a function of the corrected fan speed: N(s)/WF(s) = K/(as+1) with a=f(N)

This discovery significantly reduced the time required to design and validate the control logic Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Real-time Dynamic Engine Modeling using Computers • With increasing complexity of engines, it became too complicated to design and evaluate control logic primarily through testing.

• GRC pioneered methods to perform closed-loop (integrating control logic with the engine model) dynamic simulation using analog computers

• Simulations using Analog Computers at NACA Lewis in the 1950s • Dynamic response of a turbojet to a step fuel input From J.R. Ketchum, and R.T. Craig, “Simulation of Linearized Dynamics of Gas-turbine Engines,” NACA-TN-2826.

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Maturation of Turbine Engine Control (1970-1990) • Digital Electronic Engine Control (DEEC) • Multivariable Engine Control Development • Sensor Fault Detection, Isolation and Accommodation

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Digital Electronic Engine Control • Early 1980s NASA in collaboration with USAF and P&W conducted flight tests of DEEC on an F-100 engine • Benefits of DEEC: – increased thrust, faster response times, improved afterburner operation, improved airstart operation, elimination of ground trimming, fail-operate capability, and simplified hardware • Testing at GRC altitude test facility led to resolution of a nozzle stability and verification of a faster augmentor transient capability – Extensive PSL testing done for operation throughout the flight envelope to get clearance for flight tests on the F-15 • Flight testing at DFRC (now AFRC) demonstrated capability of digital control and led to introduction of Electronic Engine Control Units on military and commercial jets. NASA testing of DEEC was a critical step leading to current FADECs Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Multivariable Engine Control Development • AFWAL and NASA-Lewis jointly sponsored the Multivariable Control Synthesis (MVCS) program from 1975 to 1978 to investigate applicability of emerging optimal control and Linear Quadratic Regulator control theory to jet engines. • GRC developed a series of LQRs connected with simple transition logic and several operating limits to achieve effective large- transient controls. • Successful testing on an F100 engine in NASA’s altitude test facilities

F-100 LQR Control Block Diagram From: B. Lehtinen, R.L. DeHoff., and R.D. Hackney, “Multivariable Control Altitude Demonstration on the F100 Turbofan Engine,” paper presented at the 15th Joint Propulsion Conference, 1979, AIAA-79- 1204. Studies concluded that performance benefits of MVCS were not commensurate with complexity of control design and implementation Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Sensor Fault Detection, Isolation and Accommodation • In mid to late 1980s GRC investigated engine sensor failure detection approaches under the Advanced Detection, Isolation and Accommodation (ADIA) program • ADIA algorithm consisted of 3 elements: i) hard sensor failure detection and isolation logic; ii) soft sensor failure detection & isolation logic; and iii) an accommodation filter • ADIA algorithm was integrated with a microcomputer implementation of F-110 engine and a real-time evaluation was performed using a hybrid computer simulation • Transient engine operation over the full power range with a single sensor failure detection and accommodation was demonstrated on the F-100 in the PSL. • The ADIA development team received the prestigious R&D 100 award Many elements of the NASA ADIA approach are implemented in current FADECs Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Recent Significant Accomplishments (1990- 2004)

• Integrated Flight Propulsion Control Research (IFPC) • Practical Application of Multivariable Control Design • Intelligent Life Extending Control (ILEC) • High Stability Engine Control (HISTEC) • Active Stall Control

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Integrated Flight Propulsion Control Research (IFPC) • Emphasis on Advanced Short Take-Off Vertical Landing Aircraft (ASTOVL) led to investigation of IFPC concepts • GRC developed IMPAC – Integrated Methodology for Propulsion and Airframe Control and applied it to a concept ASTOVL aircraft • IMPAC based ASTOVL IFPC design was successfully demonstrated in piloted simulations in the transition flight phase

IMPAC and GRC led industry IFPC design studies helped developed various concepts that were later applicable to F-35 Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Practical Application of Multivariable Control Design • GRC IFPC research led to development of methods for practical application of Multivariable Control Design, including problem formulation using robust control design techniques, addressing controller scheduling and Integrator Wind Up Protection (IWP) IWP design and application to an engine simulation

Technologies were transferred to industry through collaborative tasks and contributed to successful application of MVC for F-135 engine Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Intelligent Life Extending Control (ILEC) • How the engine is controlled during transients has a significant impact on life of the hot gas path components • GRC research in collaboration with industry demonstrated that optimizing the engine acceleration schedule can result in significant increase in engine on-wing life Comparison of Average TMF Damage Accumulation Engine Core Speed Acceleration Response (With Varying Ambient Condition and Control Mode ) (Comparison of Original, ILEC, and Optimized Control)

4 x 10 Original ILEC Optimized

3.1 Control Control Control Schedule Schedule Schedule

3.08 Design 1.0 0.725 0.628 3.06 Condition (-27.5%) (-37.2%)

3.04 With Typical 1.132 0.826 0.718 Operating (-27.0%) (-36.6%) 3.02 Conditions

N2 Speed 3 Hot Day 1.668 1.181 0.931 2.98 Bias (-29.2%) (-44.2%) Original Schedule 2.96 ILEC schedule Cold Day 0.609 0.500 0.481 Optimized schedule Bias (-17.9%) (-21.0%) 2.94 15 15.2 15.4 15.6 15.8 16 16.2 16.4 16.6 Time On-wing life extension through “Intelligent Control” continues to be an area of interest in the industry Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field High Stability Engine Control (HISTEC) • In mid to late 1990s, GRC in collaboration with P&W, USAF, and DFRC, developed the HISTEC concept and tested it with the PW- 229 engine on a modified F-15 Aircraft

Highly successful flight test program demonstrated the capability to estimate inlet distortion and accommodate it through setting the stall margin requirement online in real time

System studies indicate that up to 2% SFC reduction can be obtained by intelligently managing the operating stall margin – continues to be an area of research Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Active Stall Control • In mid 1990s to early 2000s, there was a tremendous interest in exploring the feasibility of extending compressor operation into a higher efficiency region by using active flow control • GRC developed various technologies including stall precursor detection, optimum flow injector design, high frequency actuation. Technologies were demonstrated on a modern multi-stage compressor in collaboration with USAF and industry

Active Stall Control demonstrated with simulated recirculated flow System level benefits did not appear to be sufficient enough to warrant transition of technology to product Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Current Research (2004 Onwards)

• Model-Based Engine Control and Diagnostics • Engine Dynamic Models for Control and Diagnostics Technology Development • Distributed Engine Control (DEC) • Active Combustion Control • High Speed Propulsion System Dynamic Modeling and Control

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Model-Based Engine Controls and Diagnostics

Actuator Engine Commands Instrumentation • Fuel Flow • Pressures Actuator • Variable Geometry • Fuel flow Positions • Bleeds • Temperatures “Personalized” Engine • Rotor Speeds Control On-Board Model Selected Sensors Component & Tracking Filter Performance Estimates • Efficiencies • Flow capacities Sensor Sensor Estimates Validation & • Stability margin Fault Detection Sensor Measurements • Thrust On Board

Ground Ground-Based Diagnostics Level • Fault Codes • Maintenance/Inspection Advisories

• Real-time performance estimation • Enhanced gas path diagnostics • Performance enhancing engine control Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Model-Based Engine Control and Diagnostics • Challenge is to have an accurate enough on-board model which reflects the true condition of the engine – typically number of sensors is less than the “health parameters” in the model • GRC has developed a patented approach to determining a set of “tuners” which provide a good estimate of unmeasured engine performance and operability parameters in the presence of degradation with usage

An Integrated Architecture for Aircraft Engine Performance Monitoring and Fault Diagnostics has been developed and validated against engine test data

Feedback Parameters Fnet Fnet e Command Thrust Disturbance/ Fnet Controller Health An architecture for Model-Based Sensors Protection Actuator Engine Estimation Engine Control has been developed Logic OTKF

and demonstrated on a nonlinear Limiters e Limit SM HPC Controller HPC SM engine simulation to provide a tight Limiting Parameters control of thrust and stall margin HPC-SM Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Engine Dynamic Models for Control and Diagnostics Technology Development The following engine simulation software packages, developed in Matlab/Simulink and useful for propulsion controls and diagnostics research, are available to U.S. citizens from GRC software repository • MAPSS – Modular Aero-Propulsion System Simulation (2003) • Simulation of a modern fighter aircraft prototype engine with a basic research control law: http://sr.grc.nasa.gov/public/project/49/ • C-MAPSS – Commercial Modular Aero-Propulsion Sys Sim (2008) • Simulation of a modern commercial 90,000 lb thrust class turbofan engine with representative baseline control logic: http://sr.grc.nasa.gov/public/project/54/ • C-MAPSS40k (2010) • High fidelity simulation of a modern 40,000 lb thrust class turbofan engine with realistic baseline control logic: http://sr.grc.nasa.gov/public/project/77/ • This simulation is being used extensively in NASA sponsored propulsion control and diagnostics research, and has been downloaded by over 30 external organizations

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Commercial Modular Aero-Propulsion System Simulation 40k Simulation programmed in graphical language

C-MAPSS40k PAX200 Commercial Turbofan Engine and Controller Models

out_Nf Alt alt Alt altitude Nlp sens nf_sens Wf _act out_Nc Mach mach Nhp sens nc_sens

VSV_act out_T2 dTamb dTamb T2 sens T2_sens NcR NcR out_T24 VBV_act T24 sens T25_sens NfR NfR Mach Engine flight data Mach out_T30 Controller T30 sens T30_sens used to tune out_T50 T50 sens egt_sens Nf_zro Nf_zro out_P2 physics-based P2 sens P2_sens out_P25 Nc_zro Nc_zro model P25 sens P25_sens out_P30 P30 sens P30_sens

Simulation Inputs corrected speeds f uel f low out_P50 out_Wf Plotting and graphical P50 sens P50_sens Fdrag out_Fdrag VSV out_VSV out_Fnet analysis capability Fnet Fnet Health Parameters Engine Outputs Displays

VBV Fgross out_Fgross out_VBV

Engine Model

GUI driven operation

C-MAPSS40k thrust and stall margin response to throttle movements Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Distributed Engine Control

Objectives: • Reduce control system weight • Enable new engine performance enhancing technologies • Improve reliability • Reduce overall cost

Challenges: • High temperature electronics • Communications based on open system standards • Control function distribution Government – Industry Partnership Distributed Engine Control Working Group

Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Distributed Engine Control Modeling – Simulation – Hardware-in-the-Loop

Collaborative Environment for Development of Distributed Control Applications on the Turbine Engine

Concept

HIGH TEMPERATURE High-FidelityHigh-Fid HARDWARE Real-Time Modeling Revolutionary Controlontrool Stimulus Networkeetwotwoorkrk Controls Real-Time Target Technology

Development, SIMULATEDHMULATEDH Evolution, & ARDWAREARDWARE Sustainment Hardware-in-the-Loopp Validation Active Combustion Control Advanced Control Methods High-frequency fuel valve NL Acoustics

White Noise Instability Pressure + Pressure from + Fuel Fuel lines, Injector Fuel Modulation + Combustor Pressure Flame Valve & Combustion 6

Phase Shift Controller

Filter

Fuel delivery system model and hardware

Accumulator Combustor Instrumentation (pressures, temp’s) Modulated Modulating Fuel Flow Fuel Valve In Fuel Injector Emissions Probe Fuel Nozzle Assy Research combustor rig at UTRC

In 2005, GRC demonstrated the feasibility of active suppression of combustion instability in a realistic aero-combustion environment Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Active Combustion Control Combustion Instability Suppression Demonstrated for Low NOx Combustor Configuration (2012) Fuel Valve Dynamic Objective: Utilize Active Combustion Low Emissions Advanced Combustor Prototype Characterization Rig Control Techniques to suppress Pressure combustion instabilities. Sensor Approach: Instability suppression was demonstrated using a high-frequency Combustor fuel valve to modulate the main fuel. Fuel valve dynamic characterization rig utilized to predict actuator authority Fuel Actuator prior to combustion testing. (other side)

2 Results: NASA GRC developed Adaptive Sliding Time RMS=0.54, Mean=0 1 Controller Phasor Averaged Control able to prevent growth of 0 off combustion instability in a low emissions advanced -1 -2 Combustor Pressure Response to combustor prototype with a separate pilot and main Increasing Fuel/Air Ratio 2 fuel stage. Time RMS=0.11, Mean=0 1 Controller on Impact: Active combustion control can suppress 0 -1 combustion dynamics and allow operation of a low -2 0 5 10 15 20 25 30 35 40 emissions combustion concept at conditions that Time, sec Adaptive Sliding Phasor Averaged Control algorithm would otherwise be precluded due to unacceptably used to prevent growth of combustion instability high pressure oscillations. Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field High Speed Propulsion System Dynamic Modeling and Control • Future Supersonic aircraft are expected to be long slender body fuselage. There is potential for interaction between flexible body modes and propulsion dynamics which can negatively impact performance and ride quality – GRC is performing research in Aero-Propulso-Servo- Elasticity (APSE) - developing higher fidelity propulsion system dynamic models to investigate coupling effects with flexible modes • NASA has interest in developing hypersonic air breathing propulsion systems for low cost access to space. Air Force is interested in systems to provide rapid access to space – GRC is conducting research in Combined Cycle Engine (CCE) technologies with an emphasis on inlet design for turbine based CCE. Controls focus is on developing dynamic models and control for safe mode transition Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Aero-Propulso-Servo-Elasticity (APSE) Goals Develop dynamic propulsion system models, aero-servo-elastic & aerodynamic models, and integrate them in closed loop together with atmospheric turbulence to study the dynamic performance of supersonic vehicles for ride quality, vehicle Supersonic Concept Vehicle stability, and aerodynamic efficiency. Approach • At NASA GRC the propulsion system models are developed for a Variable Cycle Engine (VCE) based on 1D gas dynamics for engine and quasi-1D CFD for the inlet and nozzle. • Alternatively, parallel flow path modeling is developed that includes rotational flow to study dynamic performance of flow distortion. Variable cycle engine thrust response Accomplishments Nozzle frequency domain response • Developed atmospheric turbulence models, propulsion system 1D gas dynamics models, and quasi 1D inlet and nozzle models. • Developed first VCE dynamic model with feedback controls and schedules to operate continuously with varying power level. • Developed first closed loop APSE system. Inlet CFD – 2D flow field

Inlet axial pressure distribution Aero-Servo-Elastic wing displacements w/ and without propulsion system coupling

Closed loop APSE Model Hypersonic Propulsion System Control – Overview

Free-stream • Pt0 • AOA • M0 • Tt0 Geometry

Shock Set e u Position Σ Controller Point Estimator Process P2

Pivot for AoA

GRC 10-foot x 10-foot Overboard Low-speed Combined Cycle Engine (CCE) Bypass flow path Variable ramp AIP Testbed Pre-compression Bleed ducting forebody plate • Low to high speed flowpath Low-speed plug transition control • Shock positioning Low-speed flow path splitter • Fuel flow High-speed Isolator flow path High speed cowl High-speed plug High-speed flow path AIP Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field Concluding Remarks • GRC contributions to engine dynamic modeling and control technology development were critical for advancement of turbine engines, and are reflected in the modern Full Authority Digital Engine Control (FADEC) on today’s aircraft • GRC developed engine dynamic model software packages provide an important set of tools for the technical community to develop and demonstrate advanced propulsion control and diagnostics technologies • Current GRC research will enable revolutionary advances in control logic architecture – Model Based Engine Control, and control hardware architecture – Distributed Engine Control – These technologies are critical for achieving the challenging goals of increased aviation efficiency and safety, and reduced environmental impact • GRC research in high speed propulsion system dynamic modeling and control is critical to enable future supersonic aircraft and hypersonic air-breathing propulsion vehicles Glenn Research Center Intelligent Control and Autonomy Branch at Lewis Field