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A robust decomposed system control for an electro-mechanical linear actuator mechanism under input constraints
  • Mohammad Bahari,
  • Mehdi Heydari Shahna,
  • Jouni Mattila
Mohammad Bahari
Tampere University

Corresponding Author:mohammad.bahari@tuni.fi

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Mehdi Heydari Shahna
Tampere University
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Jouni Mattila
Tampere University
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Abstract

This paper aims to develop a robust decomposed system control (RDSC) strategy under input constraints for an electro-mechanical linear actuator (EMLA) with model uncertainty and external disturbances. At first, a state-space model of a complex multi-stage gearbox EMLA system, driven by a permanent magnet synchronous motor (PMSM), is developed, and the non-ideal characteristics of the ball screw are presented through the model. This results in a six-order nonlinear strict-feedback form (NSFF) system that is decomposed into three subsystems. As the paper’s main result, a novel RDSC strategy with uniform exponential stability for controlling subsystem states is presented. This developed controller avoids the “explosion of complexity” problem associated with backstepping by treating the time derivative of the virtual control input as an uncertain system term. The proposed method, while assuming load disturbances and input constraints with arbitrary bounds, offers a straightforward control approach for a broader range of applications. The controller’s performance is evaluated through the simulation of two distinct duty cycles, each representing different levels of demand on the actuator facing load disturbances near the rated motor performance.
13 Jun 2023Submitted to International Journal of Robust and Nonlinear Control
13 Jun 2023Submission Checks Completed
13 Jun 2023Assigned to Editor
13 Jun 2023Review(s) Completed, Editorial Evaluation Pending
14 Jun 2023Reviewer(s) Assigned
24 Aug 2023Editorial Decision: Revise Minor
21 Sep 20231st Revision Received
20 Nov 2023Submission Checks Completed
20 Nov 2023Assigned to Editor
20 Nov 2023Review(s) Completed, Editorial Evaluation Pending
20 Nov 2023Reviewer(s) Assigned