Technical Briefs

Sliding Mode Controller and Filter Applied to an Electrohydraulic Actuator System

[+] Author and Article Information
Shu Wang

 Eaton Corp., 14615 Lone Oak Road, Eden Prairie, MN 55344shw750@mail.usask.ca

Richard Burton

Department of Mechanical Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canadarichard.burton@usask.ca

Saeid Habibi

Department of Mechanical Engineering, McMaster University, Hamilton, ON, L8S 4L7, Canadahabibi@mcmaster.ca

J. Dyn. Sys., Meas., Control 133(2), 024504 (Feb 28, 2011) (7 pages) doi:10.1115/1.4003206 History: Received January 07, 2010; Revised August 02, 2010; Published February 28, 2011; Online February 28, 2011

A common problem pertaining to linear or nonlinear systems is the design of a combined robust control and estimation strategy that can effectively deal with noise and uncertainties. The variable structure control (VSC) and its special form of sliding mode control (SMC) demonstrate robustness with regard to uncertainties, although their performance can be severely degraded by noise. As such they can benefit from using state estimates obtained from filters. In this regard, this paper considers the use of a recently proposed robust state and parameter estimation strategy referred to as the variable structure filter (VSF) in conjunction with SMC. The contribution of this paper is a new strategy that combines sliding mode control with the variable structure filter. In the presence of bounded parametric uncertainties and noise, this combined method demonstrates robust stability both in terms of control and state estimation. Furthermore, the combined strategy can be used to achieve high regulation rates or short settling time. The combined VSF and SMC strategy is demonstrated by its application to a high precision hydrostatic system, referred to as the electrohydraulic actuator system.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

The structure and strategy of SMCF

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Figure 2

The model for the estimation phase in VSF

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Figure 3

Schematic of the EHA (19)

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Figure 4

The desired, measured, and estimated state trajectories associated with position

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Figure 5

The trajectory following error associated with position using the measured signal compared with that of the VSF state estimate

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Figure 6

The trajectory following error associated with velocity obtained by using the associated VSF state estimate (note only the estimate error is shown since the actual velocity is not known)

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Figure 7

The trajectory following error associated with acceleration obtained by using the associated VSF state estimate

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Figure 8

The measured position and its first derivative and second derivatives

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Figure 9

The measured position and its first filtered derivative and filtered second derivative and desired states

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Figure 10

The errors between derivative-filtered and desired states

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Figure 11

PID form controller designed for an EHA

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Figure 12

Desired and actual position of EHA produced by a PID controller



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