Reference Tracking of Quadrotor Using Modified Nonlinear Model Predictive Control Based on Nonlinear Disturbance Observer
Springer Proceedings in Mathematics and Statistics, ISSN: 2194-1017, Vol: 455, Page: 87-104
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
This paper proposes a modified nonlinear model predictive control based on nonlinear disturbance observer (NDO-NMPC) for reference tracking of a quadrotor. The quadrotor model is nonlinear with a multi-input-multi-output (MIMO) system type. This study’s discussed problem is requiring a quadrotor to track the given trajectories. The disturbances considered in the system are constant and step disturbances. The unknown disturbances are estimated using a nonlinear disturbance observer. Furthermore, the disturbance estimations are added to the system’s prediction of NMPC. Based on the simulation results, the NDO can provide good estimation results for estimating the system disturbances. According to the performed numerical simulations, the optimal inputs obtained satisfy the limitations of the defined constraints. In addition, the proposed NDO-NMPC can overcome external disturbances, so the outputs of NDO-NMPC are appropriate for the expected results.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85200690074&origin=inward; http://dx.doi.org/10.1007/978-981-97-2136-8_8; https://link.springer.com/10.1007/978-981-97-2136-8_8; https://dx.doi.org/10.1007/978-981-97-2136-8_8; https://link.springer.com/chapter/10.1007/978-981-97-2136-8_8
Springer Science and Business Media LLC
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