Recursive identification of Hammerstein systems with dead-zone nonlinearity in the presence of bounded noise. Issue 11 (18th August 2017)

• Record Type: Journal Article
• Authors: Zhang, Jian; Yu, Feng; Chin, KwaiSang
• Is Part Of: International journal of systems science. Volume 48:Issue 11(2017)
• Page Start: 2394
• Page End: 2404
• Publication Date: 2017-08-18
• Subjects: Recursive identification -- bounded noise -- Hammerstein system -- dead-zone nonlinearity -- convergence analysis; System analysis -- Periodicals; 003.3
• DOI: 10.1080/00207721.2017.1316427
• Languages: English
• ISSNs: 0020-7721

Abstract

ABSTRACT: The existing identification algorithms for Hammerstein systems with dead-zone nonlinearity are restricted by the noise-free condition or the stochastic noise assumption. Inspired by the practical bounded noise assumption, an improved recursive identification algorithm for Hammerstein systems with dead-zone nonlinearity is proposed. Based on the system parametric model, the algorithm is derived by minimising the feasible parameter membership set. The convergence conditions are analysed, and the adaptive weighting factor and the adaptive covariance matrix are introduced to improve the convergence. The validity of this algorithm is demonstrated by two numerical examples, including a practical DC motor case.