1. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Active and Passive Control of Compressor Flow Instabilities Active and Passive Control of Compressor Flow Instabilities February 16, 2000 J.V.R. Prasad Y. Neumeier N. Markopoulos School of Aerospace Engineering Georgia Institute of Technology Atlanta, GA 30332 School of Aerospace Engineering Georgia Institute of Technology Atlanta, GA 30332

2. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Overview Future Work Research Team Problem Statement Objectives List Of Accomplishments Significant Findings

3. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Research Team PI’s: Dr. J.V.R. Prasad Dr. Y. Neumeier Post Doctoral Fellows: Dr. N. Markopoulos Dr. M. Lal (Took up a position in ME School) Graduate Students: Mr. A. Krichene, AE, Ph.D. student Dr. C. Rivera, AE (graduated) Dr. T-Y. Ziang, AE (graduated) Mr. R. Swaminathan, AE (graduated) Mr. S. Bae, AE (graduated) Mr. A. Meehan, ME (graduated)

4. School of Aerospace Engineering MITE Problem Statement Rotating stall and surge limit the operation of modern day turbine engine compressors due to associated severe loss of performance, component failure, etc. Current practice is to limit operation with roughly 20% stall margin and limitations on fuel flow authority during acceleration and decelerations, representing loss of opportunity Active and/or passive control strategies can result in reduced stall margin that will correspond to reduced weight and fuel savings

5. School of Aerospace Engineering MITE Problem Statement (Continued)

6. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Objectives Improved understanding of compressor stall and surge phenomena through modeling, simulation and experimentation Investigation of Passive and active control mechanisms for reducing compressor stall and surge Development of hybrid control methods by combining control-theoretic and decision-theoretic techniques

7. School of Aerospace Engineering MITE School of Aerospace Engineering MITE List of Accomplishments Using theoretical extensions to Moore-Greitzer model to include finite duct effects, analytically showed that the inlet shape affects the stall inception point in axial compressors. This finding has an important bearing on the design of appropriate inlets for passive control of rotating stall. (Presented a paper at the 1999 JPC) Further experimental evaluations of passive control schemes for suppression of rotating stall. (Presented a paper at the 1999 IEEE Conference on Control Applications) Combined the backstepping control method from the literature with the adaptive neural net/fuzzy logic scheme for improving robustness of the controller and evaluated the scheme in simulations. (Presented papers at the 1999 JPC and 1999 AIAA GNC)

8. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Implemented the observer scheme for on-line identification of stall precursor waves and experimentally evaluated a novel active control scheme based on stall precursors for active surge control in the centrifugal compressor experimental facility at Georgia Tech. List of Current Year Accomplishments (Continued)

9. School of Aerospace Engineering MITE School of Aerospace Engineering MITE List of Publications 1. Prasad, J.V.R. and Jiang, T.Y., “Synthesis of Adaptive Fuzzy Logic Controllers with Control Rate and Amplitude Limits,” 1998 AIAA Guidance, Navigation and Control Conference, journal publication pending. We have recently begun work on application of this technique for an unmanned vehicle jointly with Boeing under the DARPA sponsored ‘software enabling control’ program. We have contacted Dan Gilmore of General Electric in the application of this approach to the engine fuel control problem. 2. Prasad, J.V.R., Neumeier, Y., Lal, M. and Zinn, B., “Method and Apparatus for Active Suppression of Rotating Stall and Surge in Axial Compressor through Combustion Modulations,” Invention disclosure, June 1998. On this aspect, we were recently contacted by Mr. Chris Meyer from AmTech to explore possible interest. 3. Sankar, L.N., Prasad, J.V.R., Neumeier, Y., Haddad, W.H., Markopoulos, N., Stein, A., Niazi, S., and Leonessa, A., “Recent Progress in Stall and Surge Control,” AIAA 99-0324, 17th Applied Aerodynamics Conference, Norfolk, VA, June 1999 4. Prasad, J.V.R., Neumeier, Y., Krahl, B. and Markopoulos, N., “A Computational Study of Active Control of Compressor Flow Instabilities in Turbine Engines using Fuel Flow Control,” AIAA 99-2127, Joint Propulsion Conference, Los Angeles, June 1999. 5. Markopoulos, N., Neumeier, Y., Prasad, J.V.R. and Zinn, B.T., “An Extended Analytical Model for Compressor Rotating Stall and Surge,” AIAA 99-2124, AIAA Joint Propulsion Conference, Los Angeles, June 1999. 6. Krichene, A. and Prasad, J.V.R., “Synthesis of Adaptive Neural Networks/Fuzzy Logic Based Rotating Stall Controllers for Axial Compressors,” AIAA 99-2126, Joint Propulsion Conference, Los Angeles, June 1999. 7. Prasad, J.V.R., Neumeier, Y., Lal, M., Bae, S. and meehan, A., An Experimental Investigation of Active and Passive Control of Rotating Stall in Axial Compressors, “ IEEE Conference on Control Applications, Hawaii, August 1999. 8. Krichene, A. and Prasad, J.V.R., “Synthesis of Adaptive Neural Network Based Rotating Stall Controllers for Axial Compressors,” AIAA 99-3995, AIAA Guidance, Navigation and Control Conference, Portland, August 1999.

10. School of Aerospace Engineering MITE School of Aerospace Engineering MITE List of Accomplishments Using theoretical extensions to Moore-Greitzer model to include finite duct effects, analytically showed that the inlet shape affects the stall inception point in axial compressors. This finding has an important bearing on the design of appropriate inlets for passive control of rotating stall. (Presented a paper at the 1999 JPC) Experimental evaluations of passive control schemes for suppression of rotating stall. (Presented a paper at the 1999 IEEE Conference on Control Applications) Combined the backstepping control method from the literature with the adaptive neural net/fuzzy logic scheme for improving robustness of the controller and evaluated the scheme in simulations. (Presented papers at the 1999 JPC and 1999 AIAA GNC)

11. School of Aerospace Engineering MITE School of Aerospace Engineering MITE M ODELING OF C OMPRESSOR R OTATING S TALL AND S URGE - R ECENT P ROGRESS by N. Markopoulos M ODELING OF C OMPRESSOR R OTATING S TALL AND S URGE - R ECENT P ROGRESS by N. Markopoulos

12. School of Aerospace Engineering MITE School of Aerospace Engineering MITE PREVIOUS WORK…  Complete stability analysis of the Moore-Greitzer model under stall amplitude feedback REASONS FOR THE MODELING WORK…  Moore-Greitzer model highly approximate - does not predict correct r.s. frequency, does not include effects of finite compressor length  Moore has suggested in a patent that a separator would eliminate rotating stall – we showed experimentally that this is not true  To our knowledge, there is no model that takes into account at a fundamental level of compressibility effects is available in the open literature - Mach numbers between 0.4 – 0.6  No control oriented models available for centrifugal compressors  Bottom line: Develop a basic physical understanding of the phenomena that we are trying to control

13. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Schematic of a Compressor

14. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Our model:  Moore-Greitzer model:  When Q = 0 the two models become qualitatively the same  Moore-Greitzer model is obtained as a limiting case from our model as the inlet and outlet duct lengths go to infinity  For our model stall inception occurs slightly before or beyond the peak – depending on the sign of Q, representing the effect of the inlet

15. School of Aerospace Engineering MITE School of Aerospace Engineering MITE COMPARISON WITH THE MOORE-GREITZER MODEL…  Stall inception point M-G: Ours:  Stable operation M-G: Ours:  Unstable operation M-G: Ours:  Conclude: It is very desirable to have Q > 0 for delaying loss of stability

16. School of Aerospace Engineering MITE School of Aerospace Engineering MITE  Quantitative account of instability dynamics for axial compressors - extends well-known Moore-Greitzer model  Chief difference effect of finite inlet and outlet duct lengths  What happens at entrance to inlet slightly hastens or delays settling of instabilities before or beyond peak of compressor map  Predicted r. s. frequency higher than Moore-Greitzer and function of compressor inlet length  Needed: a more fundamental account of effect of inlet in terms of inlet design parameters - future work  Brings up practical questions for the design of inlets and control of instabilities - transition to industry MAIN RESULTS ON MODELING SO FAR…

17. School of Aerospace Engineering MITE School of Aerospace Engineering MITE  Axial velocity in real compressors varies between 150 to 200 m/sec corresponding to Mach numbers between 0.4 and 0.6  Inclusion of compressibility effects into our model  Governing equation is Classical wave eq. rather than Laplace’s eq.  Implies two qualitatively different types of disturbances (bound and scattering) CURRENT WORK – AXIAL COMPRESSORS…  Disturbance analysis for purely radial flow  Disturbance theory and modeling for centrifugal compressors CURRENT WORK – CENTRIFUGAL COMPRESSORS…

18. School of Aerospace Engineering MITE School of Aerospace Engineering MITE List Accomplishments Using theoretical extensions to Moore-Greitzer model to include finite duct effects, analytically showed that the inlet shape affects the stall inception point in axial compressors. This finding has an important bearing on the design of appropriate inlets for passive control of rotating stall. (Presented a paper at the 1999 JPC) Further experimental evaluations of passive control schemes for suppression of rotating stall. (Presented a paper at the 1999 IEEE Conference on Control Applications) Combined the backstepping control method from the literature with the adaptive neural net/fuzzy logic scheme for improving robustness of the controller and evaluated the scheme in simulations. (Presented papers at the 1999 JPC and 1999 AIAA GNC)

19. School of Aerospace Engineering MITE Schematic of Experimental Set-up (Flow Separators and Flow Recirculation) Controller Pressure Measurements Servomotor and bleed Computer Bleed/recirculation loop Main Throttle

20. School of Aerospace Engineering MITE LICCHUS Axial Compressor Parameters

21. School of Aerospace Engineering MITE Flow Separators in the Inlet Moore predicted that one separator in the inlet should eliminate the rotating stall altogether ( Patent No. 5,297,930 by Moore F, K. “Rotating Stall Suppression” )

22. School of Aerospace Engineering MITE Pressure Oscillations with and without an Inlet Separator The separator seems to have no apparent effect upon the traveling waves

23. School of Aerospace Engineering MITE Effect of Eight Flow Separators on Rotating Stall Amplitude

24. School of Aerospace Engineering MITE Schematic of Flow Path a) Ambient Bleed b) Recirculation

25. School of Aerospace Engineering MITE Effect of Flow Recirculation on Rotating Stall

26. School of Aerospace Engineering MITE Effect of Flow Recirculation with Active Control on Rotating Stall

27. School of Aerospace Engineering MITE Compressor Pressure Rise versus Main Throttle Opening for Different Ambient Bleed Openings

28. School of Aerospace Engineering MITE Compressor Pressure Rise versus Normalized Flow Rate for Different Ambient Bleed Openings

29. School of Aerospace Engineering MITE Compressor Pressure Rise versus Normalized Flow Rate for Different Recirculation Bleed Openings

30. School of Aerospace Engineering MITE School of Aerospace Engineering MITE xcxc System Linear controller Model inversion Adaptive neural net/ fuzzy logic Model based controller + - + + x Adaptive Neuro-fuzzy Controller

31. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Adaptive Neuro-fuzzy Controllers Hybrid control methodology which combines model inversion with neural nets and fuzzy logic Parameterization of uncertainty using neural nets and fuzzy logic and adaptation of parameters based on Lyapunov stability theory Rule base adaptation and linear controller gain adaptation to accommodate actuator limits

32. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Model based controller Hybrid controller with fixed linear controller gain Hybrid controller with variable linear controller gain Non-dimensional time Rotating stall amplitude Response to Initial Disturbance with Model Uncertainty Controller is based on fifth order compressor map Simulation is based on third order compressor map

33. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Related Work T700 Engine Fuel Control Using Adaptive Neural networks

34. School of Aerospace Engineering MITE School of Aerospace Engineering MITE PI Network Neural F gP ZPPPTNNe,,,,,,,,0.1 45413 ad u u o u u    PREF N ECU ),:(Feedforward 2 TQr r Governor Rate Compensation and Dynamics T700 Engine HMU (Nonlinear State Feedback) - NpNp T700 Engine Fuel Controller

35. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Performance of the T700 Engine Fuel Controller Power Turbine Speed (%) Time (sec)

36. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Performance of the T700 Engine Fuel Controller to a Periodic Load Disturbance with and without adaptive neural networks

37. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Implemented the observer scheme for on-line identification of stall precursor waves and experimentally evaluated a novel active control scheme based on stall precursors for active surge control in the centrifugal compressor experimental facility at Georgia Tech. List of Accomplishments (Continued)

38. School of Aerospace Engineering MITE Centrifugal Compressor Setup Control Law Frequency/Amplitude Observer Fuel Valve Control Computer Throttle Valve servomotor Throttle and Fuel Valve Commands Data Acquisition Computer Pressure Measurements Pressure Transducer Pressures Self entraining combustor Inlet pressure readout Control Variables

39. School of Aerospace Engineering MITE Controller Essentials Utilizes real time observer that identifies the frequency and amplitude of the most dominant modes of oscillations in the inlet pressure signal Sets on-off alarm signal when precursors waves are identified with strong enough amplitude Varies the fuel flow rate or other actuators according to the alarm signal

40. School of Aerospace Engineering MITE Rejecting rather than suppressing stall Provides global stability Does not require high bandwidth actuator Can work with existing fuel injection systems Requires very little information about compressor characteristics Controller Essentials (Cont.)

41. School of Aerospace Engineering MITE Real-Time Mode Observation Low Back Pressure, 15 KRPM

42. School of Aerospace Engineering MITE Real-Time Mode Observation High Back Pressure Nearing Surge, 15 KRPM

43. School of Aerospace Engineering MITE Real-Time Mode Observation Uncontrolled Surge, 15 KRPM

44. School of Aerospace Engineering MITE Real-Time Mode Observation Uncontrolled Surge, 15 KRPM

45. School of Aerospace Engineering MITE Real-Time Mode Observation Uncontrolled Surge, 30 KRPM

46. School of Aerospace Engineering MITE Real-Time Mode Observation Uncontrolled Surge, 30 KRPM

47. School of Aerospace Engineering MITE Real-Time Mode Observation Uncontrolled Surge, 30 KRPM

48. School of Aerospace Engineering MITE Real-Time Mode Observation Uncontrolled Surge, 30 KRPM

49. School of Aerospace Engineering MITE Control Using Throttle Actuation

50. School of Aerospace Engineering MITE Control Using Throttle Actuation (Cont.)

51. School of Aerospace Engineering MITE Control Using Fuel Valve Actuation

52. School of Aerospace Engineering MITE Control Using Fuel Valve Actuation (Cont.)

53. School of Aerospace Engineering MITE School of Aerospace Engineering MITE Future Work Further theoretical, simulation (using Dr. Sankar’s CFD models) and experimental evaluations of control actuation schemes (e.g., bleed valve, fuel flow modulations, etc.) using the centrifugal compressor facility. Experimental evaluation of novel controllers. Further analysis of the effect of inlet parameters on rotating stall in axial compressors.