School of Aerospace Engineering

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

2. School of Aerospace Engineering 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) MITE

3. Problem Statement Rotating stall and surge limit the operationof 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 marginand limitations on fuel flow authority during acceleration and decelerations, representing loss of opportunity Active and/or passive control strategiescan result in reduced stall margin that will correspond to reduced weight and fuel savings

4. School of Aerospace Engineering 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 MITE

5. School of Aerospace Engineering 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) MITE

6. School of Aerospace Engineering List of Current Year Accomplishments (Continued) 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. MITE

7. School of Aerospace Engineering 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) MITE

8. School of Aerospace Engineering MODELING OF COMPRESSOR ROTATING STALL AND SURGE - RECENT PROGRESS by N. Markopoulos MITE

9. School of Aerospace Engineering • 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 MITE

10. School of Aerospace Engineering Schematic of a Compressor MITE

11. School of Aerospace Engineering • 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 MITE

12. School of Aerospace Engineering 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 MITE

13. School of Aerospace Engineering MAIN RESULTS ON MODELING SO FAR… • 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 MITE

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

15. School of Aerospace Engineering 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) MITE

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

17. 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” )

18. Pressure Oscillations with and without an Inlet Separator • The separator seems to have no apparent effect upon the traveling waves

19. Effect of Eight Flow Separators on Rotating Stall Amplitude

20. Effect of Flow Recirculation on Rotating Stall

21. Effect of Flow Recirculation with Active Control on Rotating Stall

22. Compressor Pressure Rise versus Main Throttle Opening for Different Ambient Bleed Openings

23. Compressor Pressure Rise versus Normalized Flow Rate for Different Ambient Bleed Openings

24. Compressor Pressure Rise versus Normalized Flow Rate for Different Recirculation Bleed Openings

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

26. School of Aerospace Engineering 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 MITE

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

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

29. (Feedforward r : Q , T ) r 2 u N PREF o u ad Neural 1 . 0 , e , N , N , T , P , P , P , Z Network P g 41 3 41 45 F u School of Aerospace Engineering T700 Engine Fuel Controller + Governor Rate Compensation and Dynamics HMU (Nonlinear State Feedback) u T700 Engine Np PI - - + ECU MITE

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

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

32. School of Aerospace Engineering List of Accomplishments (Continued) 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. MITE

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

34. 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

35. Controller Essentials (Cont.) • 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

36. Real-Time Mode Observation Low Back Pressure, 15 KRPM

37. Real-Time Mode Observation High Back Pressure Nearing Surge, 15 KRPM

38. Real-Time Mode Observation Uncontrolled Surge, 15 KRPM

39. Real-Time Mode Observation Uncontrolled Surge, 15 KRPM

40. Real-Time Mode Observation Uncontrolled Surge, 30 KRPM

41. Real-Time Mode Observation Uncontrolled Surge, 30 KRPM

42. Real-Time Mode Observation Uncontrolled Surge, 30 KRPM

43. Real-Time Mode Observation Uncontrolled Surge, 30 KRPM

44. Control Using Throttle Actuation

45. Control Using Throttle Actuation (Cont.)

46. Control Using Fuel Valve Actuation

47. Control Using Fuel Valve Actuation (Cont.)

48. School of Aerospace Engineering 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 parameterson rotating stall in axial compressors. MITE