Non-conventional processing of noisy signal in the adaptive control of hydraulic differential servo cylinders

Abstract

Hydraulic differential electric servo cylinders are strongly nonlinear, coupled multivariable electromechanical tools applicable for driving e.g. manipulators. The primary controllable physical agent in such systems is the time-derivative of the pressure of the working fluid in the appropriate chambers of the cylinder. Besides the nonlinearities of hydrodynamical origin discontinous ones described by the Stribeck model originate from the friction between the cylinder and the piston. This model contains the terms of the viscous, the static, and the adhesive contributions of friction. Whenever the velocity of the piston changes its sign alternating friction force of considerable amplitude appears. Such behavior means serious difficulty in feedback-based continuous path (CP) dynamic control whenever a nominal trajectory asymptotically approaching a zero velocity segment is needed: the system itself generates a noise-like acceleration signal to be used in the control. Since hydraulic drives have considerable advantages in comparison with electric ones it would be desirable to extend their application to dynamic CP control, too. For this purpose a special adaptive nonlinear control dealing with the system-generated noisy signals was elaborated. The method is rather based on a novel branch of soft computing slightly supported by a nonconventional noise filtering. The capabilities of the improved controller are illustrated via simulation.