Nonlinear adaptive learning for electrohydraulic control systems

Danian Zheng, Heather Havlicsek, Andrew Alleyne

Research output: Contribution to journalArticlepeer-review

Abstract

This investigation presents the application of an existing adaptive learning rule to the position control of a hydraulic cylinder driven by an electrohydraulic proportional valve. The system is representative of many types of Manufacturing applications including Injection Molding, Metal Forming and Industrial Presses which perform the same operation repeatedly for many cycles. The system contains several major nonlinearities that limit the ability of simple controllers in achieving satisfactory performance. These nonlinearities include: valve deadzones, valve flow saturation, and cylinder seal friction. Furthermore there is a significant compliance in the system due to the hose length between the valve and the cylinder. The learning algorithm iteratively determines an appropriate feedforward signal to be used in conjunction with simple feedback in order to track a predetermined reference signal. The algorithm is presented along with simulation and experimental results.

Original languageEnglish (US)
Pages (from-to)83-90
Number of pages8
JournalAmerican Society of Mechanical Engineers, The Fluid Power and Systems Technology Division (Publication) FPST
Volume5
StatePublished - 1998
Externally publishedYes

ASJC Scopus subject areas

  • Fluid Flow and Transfer Processes
  • Mechanical Engineering

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