Nonlinear parameter-varying embeddings for nonlinear state estimation with application to a two-link robot…

Abstract

Observer design for nonlinear systems is a relevant and challenging task in systems and control design. In this work, we follow the idea of embedding the system in the class of nonlinear parameter-varying systems to benefit from linear structures as in a standard LPV embedding while keeping some nonlinear structures and, thus, reducing the numbers of scheduling-parameters in the representation. We lay out the NLPV observer design procedure for general nonlinear systems, propose a number of improvements, and exemplify the application for a two-arm robot model. In a numerical study, we compare the performance of the NLPV design to established standard nonlinear approaches such as the \emph{extended Kalman filter} and the \emph{moving horizon estimation}.

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BibTeX RIS

BibTeX

@misc{ji2026nonlinear,
  title = {{Nonlinear parameter-varying embeddings for nonlinear state estimation with application to a two-link robot manipulator}},
  author = {Jiaxin Ji and Shivaraj Mohite and Jan Heiland},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.18603},
  eprint = {2609.18603},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.18603},
}

RIS

TY  - UNPB
TI  - Nonlinear parameter-varying embeddings for nonlinear state estimation with application to a two-link robot manipulator
AU  - Jiaxin Ji
AU  - Shivaraj Mohite
AU  - Jan Heiland
PY  - 2026
DA  - 2026/09/16
PB  - arXiv
DO  - 10.48550/arxiv.2609.18603
UR  - https://arxiv.org/abs/2609.18603
AB  - Observer design for nonlinear systems is a relevant and challenging task in systems and control design. In this work, we follow the idea of embedding the system in the class of nonlinear parameter-varying systems to benefit from linear structures as in a standard LPV embedding while keeping some nonlinear structures and, thus, reducing the numbers of scheduling-parameters in the representation. We lay out the NLPV observer design procedure for general nonlinear systems, propose a number of improvements, and exemplify the application for a two-arm robot model. In a numerical study, we compare the performance of the NLPV design to established standard nonlinear approaches such as the \emph{extended Kalman filter} and the \emph{moving horizon estimation}.
ER  -

Abstract

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