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

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

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

MOTIVATION Time Commanded Kv Actual Kv Commanded Velocity Actual Velocity Time

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

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

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

TOPIC REVIEW CATERPILLAR PATENTS NEW 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)

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

TOPIC REVIEW CATERPILLAR PATENTS 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

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

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

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

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

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

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

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

IMPROVEMENTS PUMP CONTROL 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)

Current override for unloader coil current control (ISP code) IMPROVEMENTS PUMP CONTROL Current override for unloader coil current control (ISP code)

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

IMPROVEMENTS ANTI-CAVITATION Cavitation

IMPROVEMENTS ANTI-CAVITATION Flow Sharing No Cavitation

IMPROVEMENTS LEARNING Supply KSA KSB EXTEND KAR KBR Return Boom Function

IMPROVEMENTS LEARNING Supply KSA KSB RETRACT KAR KBR Return Boom Function

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

EXPERIMENTAL RESULTS PUMP CONTROL: MARGIN

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS PUMP CONTROL: PS_SETPOINT

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

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

EXPERIMENTAL RESULTS PUMP CONTROL: MARGIN

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS PUMP CONTROL: MARGIN

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS PUMP CONTROL: PS_SETPOINT

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS icmd KV dKV NLPN EHPV Nominal inverse mapping Inverse Mapping Correction icmd KV NLPN Servo EHPV dKV FIXED Proportional Feedback

EXPERIMENTAL RESULTS PUMP CONTROL: MARGIN

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS

EXPERIMENTAL RESULTS SHOW LEARNED MAPS

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

FUTURE WORK Improve EHPV performance using adaptive proportional feedback Study convergence properties of adaptive proportional input and its impact on overall stability Incorporate fault Diagnostics capabilities along with mapping learning Refine pump controls

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

CONCLUSIONS The performance of the INCOVA control system under Ps_setpoint and margin pump control was improved when using mapping learning as oppose to using fixed inverse valve opening mapping. Satisfactory experimental results were obtained on applying feedforward learning and fixed proportional control to four (4) EHPVs Experimental verification of improved commanded velocity achievement using mapping learning was presented The need for good velocity sensor was observed (potential idea for customized sensor was presented)

CONCLUSIONS More refined code (constraints) allowed better control Unresolved Issues still exist with parameter estimation and adaptive proportional control portion Experimental validation of faster mapping learning with proportional feedback in place (fixed) Learning grid can be fixed based on curve shifting behavior

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