Synchronous Position Control of Gantry Table Using Adaptive Fraction-Order Dynamic Surface Control With Dendritic Neuron Model

Syuan Yi Chen, Zong Yue Shen

Research output: Contribution to journalArticlepeer-review

Abstract

This article introduces a three-degree-of-freedom (3DOF) model-based adaptive fractional-order dynamic surface control (AFODSC) system for a synchronous position control of a gantry table. First, the 3DOF model of the gantry table is investigated considering the rotational dynamics caused by inter-axis mechanical coupling and synchronous error. Then, a new fractional-order dynamic surface control (FODSC) approach is introduced using a fractional-order low-pass filter to provide an extra degree of freedom for the existing dynamic surface control (DSC) method. Because it is arduous to know the system uncertainty, the AFODSC is further elaborated by incorporating an adaptive mechanism and an uncertainty observation into the FODSC. In the proposed AFODSC, a modified dendritic neuron model observer (DNMO) is proposed to identify uncertainties, whereas an exponential compensator is designed to compensate for the observation error. Multiple adaptation laws are derived to adapt the parameters of DNMO on the basis of the Lyapunov stability theorem. Experimental results confirm that the proposed AFODSC system demonstrates favorable position tracking and synchronization accuracies for the gantry table compared with the conventional DSC system.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalIEEE/ASME Transactions on Mechatronics
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Adaptive control
  • Adaptive systems
  • dynamic surface control (DSC)
  • Dynamics
  • fractional order
  • gantry table
  • Neurons
  • Payloads
  • Synchronous motors
  • Tracking
  • Uncertainty

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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