Nonlinear Model Identification and Observer Design for Thrust Estimation of Small-scale Turbojet Engines
Jet-powered vertical takeoff and landing (VTOL) drones require precise thrust estimation to ensure adequate stability margins and robust maneuvering. Small-scale turbojets have become good candidates for powering heavy aerial drones. However, due to limited instrumentation available in these turboje...
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creator | Momin, Affaf Junaid Ahamad Nava, Gabriele LErario, Giuseppe Mohamed, Hosameldin Awadalla Omer Bergonti, Fabio Vanteddu, Punith Reddy Braghin, Francesco Pucci, Daniele |
description | Jet-powered vertical takeoff and landing (VTOL) drones require precise thrust
estimation to ensure adequate stability margins and robust maneuvering.
Small-scale turbojets have become good candidates for powering heavy aerial
drones. However, due to limited instrumentation available in these turbojets,
estimating the precise thrust using classical techniques is not
straightforward. In this paper, we present a methodology to accurately estimate
the online thrust for the small-scale turbojets used on the iRonCub - an aerial
humanoid robot. We use a grey-box method to capture the turbojet system
dynamics with a nonlinear state-space model based on the data acquired from a
custom engine test bench. This model is then used to design an extended Kalman
filter that estimates the turbojet thrust only from the angular speed
measurements. We exploited the parameter estimation algorithm to ensure that
the EKF gives smooth and accurate estimates even at engine failures. The
designed EKF was validated on the test bench where the mean absolute error in
estimated thrust was found to be within 2% of rated peak thrust. |
doi_str_mv | 10.48550/arxiv.2205.08330 |
format | Article |
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estimation to ensure adequate stability margins and robust maneuvering.
Small-scale turbojets have become good candidates for powering heavy aerial
drones. However, due to limited instrumentation available in these turbojets,
estimating the precise thrust using classical techniques is not
straightforward. In this paper, we present a methodology to accurately estimate
the online thrust for the small-scale turbojets used on the iRonCub - an aerial
humanoid robot. We use a grey-box method to capture the turbojet system
dynamics with a nonlinear state-space model based on the data acquired from a
custom engine test bench. This model is then used to design an extended Kalman
filter that estimates the turbojet thrust only from the angular speed
measurements. We exploited the parameter estimation algorithm to ensure that
the EKF gives smooth and accurate estimates even at engine failures. The
designed EKF was validated on the test bench where the mean absolute error in
estimated thrust was found to be within 2% of rated peak thrust.</description><identifier>DOI: 10.48550/arxiv.2205.08330</identifier><language>eng</language><subject>Computer Science - Robotics ; Computer Science - Systems and Control</subject><creationdate>2022-05</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2205.08330$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2205.08330$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Momin, Affaf Junaid Ahamad</creatorcontrib><creatorcontrib>Nava, Gabriele</creatorcontrib><creatorcontrib>LErario, Giuseppe</creatorcontrib><creatorcontrib>Mohamed, Hosameldin Awadalla Omer</creatorcontrib><creatorcontrib>Bergonti, Fabio</creatorcontrib><creatorcontrib>Vanteddu, Punith Reddy</creatorcontrib><creatorcontrib>Braghin, Francesco</creatorcontrib><creatorcontrib>Pucci, Daniele</creatorcontrib><title>Nonlinear Model Identification and Observer Design for Thrust Estimation of Small-scale Turbojet Engines</title><description>Jet-powered vertical takeoff and landing (VTOL) drones require precise thrust
estimation to ensure adequate stability margins and robust maneuvering.
Small-scale turbojets have become good candidates for powering heavy aerial
drones. However, due to limited instrumentation available in these turbojets,
estimating the precise thrust using classical techniques is not
straightforward. In this paper, we present a methodology to accurately estimate
the online thrust for the small-scale turbojets used on the iRonCub - an aerial
humanoid robot. We use a grey-box method to capture the turbojet system
dynamics with a nonlinear state-space model based on the data acquired from a
custom engine test bench. This model is then used to design an extended Kalman
filter that estimates the turbojet thrust only from the angular speed
measurements. We exploited the parameter estimation algorithm to ensure that
the EKF gives smooth and accurate estimates even at engine failures. The
designed EKF was validated on the test bench where the mean absolute error in
estimated thrust was found to be within 2% of rated peak thrust.</description><subject>Computer Science - Robotics</subject><subject>Computer Science - Systems and Control</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj01OwzAYRL1hgQoHYIUvkGDHduMsUSlQqaULso_887k1cm1kpxXcnrRlNRpp9DQPoQdKai6FIE8q__hT3TRE1EQyRm7R_iPF4COojDfJQsArC3H0zhs1-hSxihZvdYF8goxfoPhdxC5l3O_zsYx4WUZ_uC6Tw58HFUJVjAqA-2PW6QumSdxN_HKHbpwKBe7_c4b612W_eK_W27fV4nldqXlLKgOcGBBGGMqBcKuFlK1wBIxhILmUnaSy4Q3hc6tpK7tOMUsF1Zobei4z9HjFXlSH7zzdy7_DWXm4KLM_5jFSJg</recordid><startdate>20220517</startdate><enddate>20220517</enddate><creator>Momin, Affaf Junaid Ahamad</creator><creator>Nava, Gabriele</creator><creator>LErario, Giuseppe</creator><creator>Mohamed, Hosameldin Awadalla Omer</creator><creator>Bergonti, Fabio</creator><creator>Vanteddu, Punith Reddy</creator><creator>Braghin, Francesco</creator><creator>Pucci, Daniele</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20220517</creationdate><title>Nonlinear Model Identification and Observer Design for Thrust Estimation of Small-scale Turbojet Engines</title><author>Momin, Affaf Junaid Ahamad ; Nava, Gabriele ; LErario, Giuseppe ; Mohamed, Hosameldin Awadalla Omer ; Bergonti, Fabio ; Vanteddu, Punith Reddy ; Braghin, Francesco ; Pucci, Daniele</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a670-ce40ce5c5c14e04db58875f0ecc3e84889818242046db17899a3d151bb4c199a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Computer Science - Robotics</topic><topic>Computer Science - Systems and Control</topic><toplevel>online_resources</toplevel><creatorcontrib>Momin, Affaf Junaid Ahamad</creatorcontrib><creatorcontrib>Nava, Gabriele</creatorcontrib><creatorcontrib>LErario, Giuseppe</creatorcontrib><creatorcontrib>Mohamed, Hosameldin Awadalla Omer</creatorcontrib><creatorcontrib>Bergonti, Fabio</creatorcontrib><creatorcontrib>Vanteddu, Punith Reddy</creatorcontrib><creatorcontrib>Braghin, Francesco</creatorcontrib><creatorcontrib>Pucci, Daniele</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Momin, Affaf Junaid Ahamad</au><au>Nava, Gabriele</au><au>LErario, Giuseppe</au><au>Mohamed, Hosameldin Awadalla Omer</au><au>Bergonti, Fabio</au><au>Vanteddu, Punith Reddy</au><au>Braghin, Francesco</au><au>Pucci, Daniele</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Nonlinear Model Identification and Observer Design for Thrust Estimation of Small-scale Turbojet Engines</atitle><date>2022-05-17</date><risdate>2022</risdate><abstract>Jet-powered vertical takeoff and landing (VTOL) drones require precise thrust
estimation to ensure adequate stability margins and robust maneuvering.
Small-scale turbojets have become good candidates for powering heavy aerial
drones. However, due to limited instrumentation available in these turbojets,
estimating the precise thrust using classical techniques is not
straightforward. In this paper, we present a methodology to accurately estimate
the online thrust for the small-scale turbojets used on the iRonCub - an aerial
humanoid robot. We use a grey-box method to capture the turbojet system
dynamics with a nonlinear state-space model based on the data acquired from a
custom engine test bench. This model is then used to design an extended Kalman
filter that estimates the turbojet thrust only from the angular speed
measurements. We exploited the parameter estimation algorithm to ensure that
the EKF gives smooth and accurate estimates even at engine failures. The
designed EKF was validated on the test bench where the mean absolute error in
estimated thrust was found to be within 2% of rated peak thrust.</abstract><doi>10.48550/arxiv.2205.08330</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Robotics Computer Science - Systems and Control |
title | Nonlinear Model Identification and Observer Design for Thrust Estimation of Small-scale Turbojet Engines |
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