Discrete-Time Incremental Backstepping Control with Extended Kalman Filter for UAVs
In this study, a discrete-time incremental backstepping (DTIBS) controller with an extended Kalman filter (EKF) is proposed for unmanned aerial vehicles (UAVs) with unknown actuator dynamics. The Taylor series and an approximate discrete method are employed, transforming the second-order continuous-...
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| Veröffentlicht in: | Electronics (Basel) 2023-07, Vol.12 (14), p.3079 |
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| creator | Liu, Yanju Duan, Chengyu Liu, Lei Cao, Lijia |
| description | In this study, a discrete-time incremental backstepping (DTIBS) controller with an extended Kalman filter (EKF) is proposed for unmanned aerial vehicles (UAVs) with unknown actuator dynamics. The Taylor series and an approximate discrete method are employed, transforming the second-order continuous-time nonlinear system into a discrete-time nonlinear plant with an incremental input form. The incremental control laws are designed using the incremental nonlinear dynamic inversion (INDI) method and the time-delay control (TDC) method. The TDC is introduced to design the control law, eliminating the need for prior knowledge of the control effectiveness matrix involving some unknown aerodynamic coefficients. In addition, the airflow angle and body rotation rate are selected as key system states, and the EKF is used to design a state estimator to estimate the local state of the small unmanned aerial vehicle closed-loop flight control system under strong noise conditions. The effectiveness of the DTIBS control method with EKF is verified through numerical simulation. The results show that the proposed method can effectively estimate the state under the typical noise characteristics of low-cost sensors, and the closed-loop control systems has good tracking performance and can quickly and effectively track sudden commands. |
| doi_str_mv | 10.3390/electronics12143079 |
| format | Article |
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The Taylor series and an approximate discrete method are employed, transforming the second-order continuous-time nonlinear system into a discrete-time nonlinear plant with an incremental input form. The incremental control laws are designed using the incremental nonlinear dynamic inversion (INDI) method and the time-delay control (TDC) method. The TDC is introduced to design the control law, eliminating the need for prior knowledge of the control effectiveness matrix involving some unknown aerodynamic coefficients. In addition, the airflow angle and body rotation rate are selected as key system states, and the EKF is used to design a state estimator to estimate the local state of the small unmanned aerial vehicle closed-loop flight control system under strong noise conditions. The effectiveness of the DTIBS control method with EKF is verified through numerical simulation. The results show that the proposed method can effectively estimate the state under the typical noise characteristics of low-cost sensors, and the closed-loop control systems has good tracking performance and can quickly and effectively track sudden commands.</description><identifier>ISSN: 2079-9292</identifier><identifier>EISSN: 2079-9292</identifier><identifier>DOI: 10.3390/electronics12143079</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Actuators ; Aerodynamic coefficients ; Air flow ; Aircraft ; Closed loop systems ; Closed loops ; Continuous time systems ; Control algorithms ; Control methods ; Control theory ; Controllers ; Design ; Discrete time systems ; Dynamic inversion ; Dynamical systems ; Extended Kalman filter ; Feedback control ; Flight control systems ; Mathematical models ; Methods ; Miniature aircraft ; Nonlinear dynamics ; Nonlinear systems ; Robust control ; Rotating bodies ; Sensors ; Simulation ; State estimation ; System effectiveness ; Taylor series ; Tracking control ; Unmanned aerial vehicles</subject><ispartof>Electronics (Basel), 2023-07, Vol.12 (14), p.3079</ispartof><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c322t-43cc54f15f39867acfca0dded3d77527cac98126e2671efb4cd40ce90e0434a83</citedby><cites>FETCH-LOGICAL-c322t-43cc54f15f39867acfca0dded3d77527cac98126e2671efb4cd40ce90e0434a83</cites><orcidid>0000-0002-3074-4727</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Liu, Yanju</creatorcontrib><creatorcontrib>Duan, Chengyu</creatorcontrib><creatorcontrib>Liu, Lei</creatorcontrib><creatorcontrib>Cao, Lijia</creatorcontrib><title>Discrete-Time Incremental Backstepping Control with Extended Kalman Filter for UAVs</title><title>Electronics (Basel)</title><description>In this study, a discrete-time incremental backstepping (DTIBS) controller with an extended Kalman filter (EKF) is proposed for unmanned aerial vehicles (UAVs) with unknown actuator dynamics. The Taylor series and an approximate discrete method are employed, transforming the second-order continuous-time nonlinear system into a discrete-time nonlinear plant with an incremental input form. The incremental control laws are designed using the incremental nonlinear dynamic inversion (INDI) method and the time-delay control (TDC) method. The TDC is introduced to design the control law, eliminating the need for prior knowledge of the control effectiveness matrix involving some unknown aerodynamic coefficients. In addition, the airflow angle and body rotation rate are selected as key system states, and the EKF is used to design a state estimator to estimate the local state of the small unmanned aerial vehicle closed-loop flight control system under strong noise conditions. The effectiveness of the DTIBS control method with EKF is verified through numerical simulation. The results show that the proposed method can effectively estimate the state under the typical noise characteristics of low-cost sensors, and the closed-loop control systems has good tracking performance and can quickly and effectively track sudden commands.</description><subject>Actuators</subject><subject>Aerodynamic coefficients</subject><subject>Air flow</subject><subject>Aircraft</subject><subject>Closed loop systems</subject><subject>Closed loops</subject><subject>Continuous time systems</subject><subject>Control algorithms</subject><subject>Control methods</subject><subject>Control theory</subject><subject>Controllers</subject><subject>Design</subject><subject>Discrete time systems</subject><subject>Dynamic inversion</subject><subject>Dynamical systems</subject><subject>Extended Kalman filter</subject><subject>Feedback control</subject><subject>Flight control systems</subject><subject>Mathematical models</subject><subject>Methods</subject><subject>Miniature aircraft</subject><subject>Nonlinear dynamics</subject><subject>Nonlinear systems</subject><subject>Robust control</subject><subject>Rotating bodies</subject><subject>Sensors</subject><subject>Simulation</subject><subject>State estimation</subject><subject>System effectiveness</subject><subject>Taylor series</subject><subject>Tracking control</subject><subject>Unmanned aerial vehicles</subject><issn>2079-9292</issn><issn>2079-9292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNptkE9LAzEUxIMoWGo_gZeA59X822ZzrLXVYsGDrdclZl80dTe7JinqtzdSDx58l3kDwwz8EDqn5JJzRa6gBZNC752JlFHBiVRHaMSyFIopdvznP0WTGHckn6K84mSEHm9cNAESFBvXAV75bDrwSbf4Wpu3mGAYnH_B897njRZ_uPSKF58JfAMNvtdtpz1eujZBwLYPeDt7imfoxOo2wuRXx2i7XGzmd8X64XY1n60LwxlLheDGlMLS0nJVTaU21mjS5FreSFkyabRRFWVTYFNJwT4L0whiQBEgggtd8TG6OPQOoX_fQ0z1rt8HnydrVmUOpRCS5xQ_pEzoYwxg6yG4ToevmpL6B2D9D0D-DZyrZyU</recordid><startdate>20230701</startdate><enddate>20230701</enddate><creator>Liu, Yanju</creator><creator>Duan, Chengyu</creator><creator>Liu, Lei</creator><creator>Cao, Lijia</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PIMPY</scope><scope>PKEHL</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-3074-4727</orcidid></search><sort><creationdate>20230701</creationdate><title>Discrete-Time Incremental Backstepping Control with Extended Kalman Filter for UAVs</title><author>Liu, Yanju ; Duan, Chengyu ; Liu, Lei ; Cao, Lijia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c322t-43cc54f15f39867acfca0dded3d77527cac98126e2671efb4cd40ce90e0434a83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Actuators</topic><topic>Aerodynamic coefficients</topic><topic>Air flow</topic><topic>Aircraft</topic><topic>Closed loop systems</topic><topic>Closed loops</topic><topic>Continuous time systems</topic><topic>Control algorithms</topic><topic>Control methods</topic><topic>Control theory</topic><topic>Controllers</topic><topic>Design</topic><topic>Discrete time systems</topic><topic>Dynamic inversion</topic><topic>Dynamical systems</topic><topic>Extended Kalman filter</topic><topic>Feedback control</topic><topic>Flight control systems</topic><topic>Mathematical models</topic><topic>Methods</topic><topic>Miniature aircraft</topic><topic>Nonlinear dynamics</topic><topic>Nonlinear systems</topic><topic>Robust control</topic><topic>Rotating bodies</topic><topic>Sensors</topic><topic>Simulation</topic><topic>State estimation</topic><topic>System effectiveness</topic><topic>Taylor series</topic><topic>Tracking control</topic><topic>Unmanned aerial vehicles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Yanju</creatorcontrib><creatorcontrib>Duan, Chengyu</creatorcontrib><creatorcontrib>Liu, Lei</creatorcontrib><creatorcontrib>Cao, Lijia</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Electronics (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Yanju</au><au>Duan, Chengyu</au><au>Liu, Lei</au><au>Cao, Lijia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Discrete-Time Incremental Backstepping Control with Extended Kalman Filter for UAVs</atitle><jtitle>Electronics (Basel)</jtitle><date>2023-07-01</date><risdate>2023</risdate><volume>12</volume><issue>14</issue><spage>3079</spage><pages>3079-</pages><issn>2079-9292</issn><eissn>2079-9292</eissn><abstract>In this study, a discrete-time incremental backstepping (DTIBS) controller with an extended Kalman filter (EKF) is proposed for unmanned aerial vehicles (UAVs) with unknown actuator dynamics. The Taylor series and an approximate discrete method are employed, transforming the second-order continuous-time nonlinear system into a discrete-time nonlinear plant with an incremental input form. The incremental control laws are designed using the incremental nonlinear dynamic inversion (INDI) method and the time-delay control (TDC) method. The TDC is introduced to design the control law, eliminating the need for prior knowledge of the control effectiveness matrix involving some unknown aerodynamic coefficients. In addition, the airflow angle and body rotation rate are selected as key system states, and the EKF is used to design a state estimator to estimate the local state of the small unmanned aerial vehicle closed-loop flight control system under strong noise conditions. The effectiveness of the DTIBS control method with EKF is verified through numerical simulation. The results show that the proposed method can effectively estimate the state under the typical noise characteristics of low-cost sensors, and the closed-loop control systems has good tracking performance and can quickly and effectively track sudden commands.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/electronics12143079</doi><orcidid>https://orcid.org/0000-0002-3074-4727</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Actuators Aerodynamic coefficients Air flow Aircraft Closed loop systems Closed loops Continuous time systems Control algorithms Control methods Control theory Controllers Design Discrete time systems Dynamic inversion Dynamical systems Extended Kalman filter Feedback control Flight control systems Mathematical models Methods Miniature aircraft Nonlinear dynamics Nonlinear systems Robust control Rotating bodies Sensors Simulation State estimation System effectiveness Taylor series Tracking control Unmanned aerial vehicles |
| title | Discrete-Time Incremental Backstepping Control with Extended Kalman Filter for UAVs |
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