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Synthesis of a New Robust Exponential Sliding Mode Differentiator with its Observer Applications
Author(s) -
Deepika Deepika,
Narayan Shiv,
Kaur Sandeep
Publication year - 2019
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1943
Subject(s) - differentiator , robustness (evolution) , control theory (sociology) , exponential function , state observer , observer (physics) , convergence (economics) , computer science , mode (computer interface) , mathematics , nonlinear system , mathematical analysis , artificial intelligence , bandwidth (computing) , physics , computer network , biochemistry , chemistry , control (management) , quantum mechanics , economics , gene , economic growth , operating system
This paper proposes a new robust exponential sliding mode differentiator for estimating the ( n − 1) derivatives of a non‐linear function. Finite time convergence, robustness, and exactness are also ensured analytically with the proposed methodology. In addition, the results of the proposed sliding mode differentiator are extended to derive theorems for the novel state (SO) and extended state observers (ESO), which would estimate the system states as well as uncertainties recursively in finite time. Finally, three examples are implemented to validate the proposed methodologies and the obtained simulations are compared with the previously developed methods in literature.