Design of cross-coupled cmac for contour-following – a reinforcement-based ilc approach

Wei Liang Kuo, Ming Yang Cheng, Wei Che Tsai

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

One of the most popular applications of a bi-axial motion stage is precision motion control. The reduction of tracking error and contour error is one of the most coveted goals in precision motion control systems. The accuracy of a motion control system is often affected by external disturbances. In addition, system non-linearity such as friction also represents a major hurdle to motion precision. In order to deal with the aforementioned problem, this paper proposes a fuzzy logic-based Reinforcement Iterative Learning Control (RILC) and a Cross-Coupled Cerebellar Model Articulation Controller (CCCMAC). In particular, the proposed fuzzy logic-based RILC and a LuGre friction model-based compensation approach are exploited to improve motion accuracy. The fuzzy logic-based RILC aims at reducing tracking error and compensating for external disturbance, while the LuGre friction model is responsible for friction compensation. In addition, the CCCMAC consisting of a cerebellar model articulation controller and a cross-coupled controller aims at reducing contour error and dealing with the problem of dynamics mismatch between different axes. Performance comparisons between the proposed fuzzy logic-based Reinforcement Iterative Learning Cross-Coupled Cerebellar Model Articulation Controller (RIL–CCCMAC) and several existing control schemes are conducted on a bi-axial motion stage. Experimental results verify the effectiveness of the proposed RIL–CCCMAC.

Original languageEnglish
Pages (from-to)302-311
Number of pages10
JournalAutomatika
Volume58
Issue number3
DOIs
Publication statusPublished - 2017

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

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