Adaptive neural dynamic surface control for servo systems with unknown dead-zone

J Na, X. Ren, G Herrmann, Z. Qiao

Research output: Contribution to journalArticle (Academic Journal)peer-review

108 Citations (Scopus)

Abstract

An adaptive neural controller is proposed for nonlinear systems with a nonlinear dead-zone and multiple time-delays. The often used inverse model compensation approach is avoided by representing the dead-zone as a time-varying system. The “explosion of complexity” in the backstepping synthesis is eliminated in terms of the dynamic surface control (DSC) technique. A novel high-order neural network (HONN) with only a scalar weight parameter is developed to account for unknown nonlinearities. The control singularity and some restrictive requirements on the system are circumvented. Simulations and experiments for a turntable servo system with permanent-magnet synchronous motor (PMSM) are provided to verify the reliability and effectiveness.
Translated title of the contributionAdaptive neural dynamic surface control for servo systems with unknown dead-zone
Original languageEnglish
Pages (from-to)1328 - 1343
Number of pages16
JournalControl Engineering Practice
Volume19(11)
DOIs
Publication statusPublished - Aug 2011

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