1 / 68

AUTO-CALIBRATION AND CONTROL APPLIED TO ELECTRO-HYDRAULIC VALVES

AUTO-CALIBRATION AND CONTROL APPLIED TO ELECTRO-HYDRAULIC VALVES. PATRICK OPDENBOSCH Graduate Research Intern INCOVA (262) 513 4408 patrick.opdenbosch@huscointl.com. EXPERIMENTS ON HUSCO BLUE TELEHANDLER August 18, 2006. HUSCO International W239 N218 Pewaukee Rd. Waukesha, WI 53188-1638.

candace-cantrell
Download Presentation

AUTO-CALIBRATION AND CONTROL APPLIED TO ELECTRO-HYDRAULIC VALVES

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. AUTO-CALIBRATION AND CONTROL APPLIED TO ELECTRO-HYDRAULIC VALVES PATRICK OPDENBOSCH Graduate Research Intern INCOVA (262) 513 4408 patrick.opdenbosch@huscointl.com EXPERIMENTS ON HUSCO BLUE TELEHANDLERAugust 18, 2006 HUSCO International W239 N218 Pewaukee Rd. Waukesha, WI 53188-1638

  2. MOTIVATION Hierarchical control: System controller, pressure controller, function controller HUSCO’S CONTROL TOPOLOGY US PATENT # 6,732,512 & 6,718,759 Steady State Mapping (Design) Inverse Mapping (Control) HUSCO OPEN LOOP CONTROL FOR EHPV’s

  3. MOTIVATION Hierarchical control: System controller, pressure controller, function controller HUSCO’S CONTROL TOPOLOGY US PATENT # 6,732,512 & 6,718,759 Steady State Mapping (Design) Inverse Mapping (Control)

  4. MOTIVATION Time Commanded Kv Actual Kv Commanded Velocity Actual Velocity Time

  5. MOTIVATION • Flow conductance online estimation • Accuracy • Computation effort • Online inverse flow conductance mapping learning and control • Effects by input saturation and time-varying dynamics • Maintain tracking error dynamics stable while learning • Fault diagnostics • How can the learned mappings be used for fault detection

  6. PRESENTATION OUTLINE • MOTIVATION • TOPIC REVIEW • SETUP • IMPROVEMENTS • MAPPING LEARNING & CONTROL • EXPERIMENTAL RESULTS • FUTURE WORK • CONCLUSIONS

  7. TOPIC REVIEW • PURDUE PAPERS • Liu, S. and Yao, B., (2005), Automated modeling of cartridge valve flow mapping, in Proc: IEEE/ASME International Conference on Advanced Intelligent Mechatronics pp. 789-794 • Liu, S. and Yao, B., (2005), On-board system identification of systems with unknown input nonlinearity and system parameters, in Proc: ASME International Mechanical Engineering Congress and Exposition • Liu, S. and Yao, B., (2005), Sliding mode flow rate observer design, in Proc: Sixth International Conference on Fluid Power Transmission and Control pp. 69-73

  8. TOPIC REVIEW • CATERPILLAR PATENTS • Aardema, J.A. and Koehler, D.W., (1999) System and method for controlling an independent metering valve, U.S. Patent (5,960,695) • Aardema, J.A. and Koehler, D.W., (1999) System and method for controlling an independent metering valve, U.S. Patent (5,947,140) • Kozaki, T., Ishikawa, H., Yasui, H., et al., (1991) Position control device and automotive suspension system employing same, U.S. Patent (5,004,264) NEW PATENTS • Reedy, J.T., Cone, R.D., Kloeppel, G.R., et al., (2006) Adaptive position determining system for hydraulic cylinder, U.S. Patent (20060064971) • Du, H., (2006) Hydraulic system health indicator, U.S. Patent (7,043,975) • Wear, J.A., Du, H., Ferkol, G.A., et al., (2006) Electrohydraulic control system, U.S. Patent (20060095163)

  9. TOPIC REVIEW • CATERPILLAR PATENTS • 20060064971 “Adaptive Position Determining System for Hydraulic Cylinder” Limit Switches

  10. TOPIC REVIEW Long-Jang Li, US Patent 5,942,892 (1999) • CATERPILLAR PATENTS • 5,004,264 “Position Control Device and Automotive Suspension System Employing Same” Position Detector

  11. TOPIC REVIEW • CATERPILLAR PATENTS • 20060095163 “Electrohydraulic Control System” Position/Velocity sensor Adaptive scheme: no details found

  12. TOPIC REVIEW • CATERPILLAR PATENTS • 7,043,975 “Hydraulic System Health Indicator” Using Lyapunov stability theory Health Monitoring using Bulk modulus and other model-based parameters (Position/velocity sensor) Based on pump pressure discharge dynamics or cylinder head end control pressure

  13. PRESENTATION OUTLINE • MOTIVATION • TOPIC REVIEW • SETUP • IMPROVEMENTS • MAPPING LEARNING & CONTROL • EXPERIMENTAL RESULTS • FUTURE WORK • CONCLUSIONS

  14. SETUP • MOTION CONTROL • Independent coil current control • SIEMENS controller • Supply & return pressure from ISP Supply KSA KSB HUSCO Blue Telehandler KAR KBR Return Boom Function Boom Function Kinematics

  15. Pump KSA KSB Unloader Diesel Engine Relief Valve KAR KBR Boom Cylinder Filter Tank SETUP • MOTION CONTROL • Independent coil current control • SIEMENS controller • Supply & return pressure from ISP PS HUSCO Blue Telehandler PB PA PR

  16. PRESENTATION OUTLINE • MOTIVATION • TOPIC REVIEW • SETUP • IMPROVEMENTS • MAPPING LEARNING & CONTROL • EXPERIMENTAL RESULTS • FUTURE WORK • CONCLUSIONS

  17. IMPROVEMENTS • PUMP CONTROL Ripples Pressure override for pump pressure control (ISP code)

  18. IMPROVEMENTS DATA SHOWN: Margin added on retract metering mode (PB signal is user commanded, not actual workport pressure) • PUMP CONTROL Current override for unloader coil current control (ISP code)

  19. IMPROVEMENTS • ANTI-CAVITATION KOUT_MAX m = R3/4 PIN_MIN Unconstrained Operating Point Keq_dPmin KIN_MAX Keq POUT_MAX Constrained Operating Point

  20. IMPROVEMENTS • ANTI-CAVITATION Cavitation

  21. IMPROVEMENTS • ANTI-CAVITATION Flow Sharing No Cavitation

  22. IMPROVEMENTS • LEARNING Supply KSA KSB EXTEND KAR KBR Return Boom Function

  23. IMPROVEMENTS • LEARNING Supply KSA KSB RETRACT KAR KBR Return Boom Function

  24. IMPROVEMENTS • LEARNING Supply KSA KSB EXTEND/RETRACT KAR KBR Return Boom Function

  25. PRESENTATION OUTLINE • MOTIVATION • TOPIC REVIEW • SETUP • IMPROVEMENTS • MAPPING LEARNING & CONTROL • EXPERIMENTAL RESULTS • FUTURE WORK • CONCLUSIONS

  26. MAPPING LEARNING & CONTROL • LEARNING APPLIED TO NONLINEAR SYSTEM • MAPPING TO BE LEARNED (simplified) Expected curve shift

  27. MAPPING LEARNING & CONTROL • LEARNING APPLIED TO NONLINEAR SYSTEM • MAPPING TO BE LEARNED (simplified) Expected curve shift

  28. MAPPING LEARNING & CONTROL • LEARNING APPLIED TO NONLINEAR SYSTEM • CONTROL DESIGN • Tracking Error: • Error Dynamics: Linear Time Varying System

  29. MAPPING LEARNING & CONTROL • LEARNING APPLIED TO NONLINEAR SYSTEM • CONTROL DESIGN • Error Dynamics: • Deadbeat Control Law: • Closed loop

  30. MAPPING LEARNING & CONTROL • LEARNING APPLIED TO NONLINEAR SYSTEM • CONTROL DESIGN • Deadbeat Control Law: • Proposed Control Law:

  31. MAPPING LEARNING & CONTROL Nominal inverse mapping Inverse Mapping Correction icmd KV Servo EHPV NLPN dKV Adaptive Proportional Feedback Jacobian Controllability Estimation

  32. MAPPING LEARNING & CONTROL • LEARNING APPLIED TO NONLINEAR SYSTEM • CONTROL DESIGN • Proposed Control Law: • Closed loop

  33. MAPPING LEARNING & CONTROL • IDENTIFICATION DESIGN • Methods: • Least Squares (Recursive) • Noise rejection • Poor time varying parameter tracking capabilities (add covariance reset and forgetting factor – dynamic or static) • New research suggest variable-length moving window* • Gradient Based • Sensitive to noise • Better time varying parameter tracking capabilities • Gradient step size must be chosen carefully Identification of time varying parameter for a linear system (*) Jiang, J. and Zhang, Y. (2004), A Novel Variable-Length Sliding Window Blockwise Least-Squares Algorithm for Online Estimation of Time-Varying Parameters, Intl. J. Adaptive Ctrl & Signal Proc., Vol 18, No. 6, pp. 505-521.

  34. MAPPING LEARNING & CONTROL • IDENTIFICATION DESIGN • Approximations: • Previous-point Linearization • Stack Operator

  35. MAPPING LEARNING & CONTROL • IDENTIFICATION DESIGN • Approximations: • Previous-point Linearization • Stack Operator Properties

  36. MAPPING LEARNING & CONTROL • IDENTIFICATION DESIGN • Approximations: • Previous-point Linearization • Stack Operator Properties

  37. MAPPING LEARNING & CONTROL • IDENTIFICATION DESIGN • Approximations: • Previous-point Linearization

  38. MAPPING LEARNING & CONTROL • IDENTIFICATION DESIGN • Approximations: • Previous-point Linearization How are (dJ,dQ) and (J*,Q*) related?

  39. PRESENTATION OUTLINE • MOTIVATION • TOPIC REVIEW • SETUP • IMPROVEMENTS • MAPPING LEARNING & CONTROL • EXPERIMENTAL RESULTS • FUTURE WORK • CONCLUSIONS

  40. EXPERIMENTAL RESULTS Nominal inverse mapping icmd KV Servo EHPV dKV Every valve uses a generic Table

  41. EXPERIMENTAL RESULTS • PUMP CONTROL: MARGIN

  42. EXPERIMENTAL RESULTS

  43. EXPERIMENTAL RESULTS

  44. EXPERIMENTAL RESULTS • PUMP CONTROL: PS_SETPOINT

  45. EXPERIMENTAL RESULTS

  46. EXPERIMENTAL RESULTS

  47. EXPERIMENTAL RESULTS Nominal inverse mapping Inverse Mapping Correction icmd KV Servo EHPV NLPN dKV

  48. EXPERIMENTAL RESULTS • PUMP CONTROL: MARGIN

  49. EXPERIMENTAL RESULTS

  50. EXPERIMENTAL RESULTS

More Related