This preprint is under consideration at Nonlinear Dynamics. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
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Research Article
Zhang Chuanlin
Shanghai University of Electric Power
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6052-1682
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This work is licensed under a CC BY 4.0 License. Read Full License
This paper proposes a non-recursive adaptive control scheme for a class of lower-triangular nonlinear systems with mismatched time-varying disturbances. As a result, an exact tracking control scheme is constructed straightforwardly from the system in a novel non-recursive synthesis manner. Firstly, with the help of higher-order sliding mode observer (HOSMO), the original system is delicately transformed into an equivalent stabilizable system. Then, a non-recursive stabilizer with a simple update mechanism for the dynamic gain can be derived. Subsequently, a rigorous stability analysis shows the theoretical justification of the proposed design framework. New characteristics of the proposed algorithm are mainly twofold: 1) The proposed adaption mechanism could substantially adjust the transient-time performance with the presence of different levels of disturbances. 2) The composite control design procedure is essentially detached with stability analysis, which could largely facilitate practical implementations.
Keywords
adaption mechanism, mismatched disturbances, higher-order sliding mode observer, lowertriangular nonlinear system
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CURRENT STATUS: Under Review
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Posted 10 Mar, 2021
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Received 07 Mar, 2021
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Subject Areas
Developmental Neuroscience
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This preprint is under consideration at Nonlinear Dynamics. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Zhang Chuanlin
Shanghai University of Electric Power
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6052-1682
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 10 Mar, 2021
No community comments so far
Review #? received
Received 07 Mar, 2021
Reviewers invited
Invitations sent on 07 Mar, 2021
Editor assigned
On 15 Feb, 2021
First submitted
On 10 Feb, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Developmental Neuroscience
License:
This work is licensed under a CC BY 4.0 License. Read Full License
This paper proposes a non-recursive adaptive control scheme for a class of lower-triangular nonlinear systems with mismatched time-varying disturbances. As a result, an exact tracking control scheme is constructed straightforwardly from the system in a novel non-recursive synthesis manner. Firstly, with the help of higher-order sliding mode observer (HOSMO), the original system is delicately transformed into an equivalent stabilizable system. Then, a non-recursive stabilizer with a simple update mechanism for the dynamic gain can be derived. Subsequently, a rigorous stability analysis shows the theoretical justification of the proposed design framework. New characteristics of the proposed algorithm are mainly twofold: 1) The proposed adaption mechanism could substantially adjust the transient-time performance with the presence of different levels of disturbances. 2) The composite control design procedure is essentially detached with stability analysis, which could largely facilitate practical implementations.
Figure 1
Figure 2
This preprint is available for download as a PDF.
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