Performance enhancement of an uncertain nonlinear medical robot with optimal nonlinear robust controller

Cardiopulmonary resuscitation refers to the process of sending oxygen and blood to the body's vital organs during cardiac arrest. For this reason, designing and controlling an accurate robot is crucial to saving the lives of patients. This study aims to optimize two nonlinear robust controllers...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computers in biology and medicine 2022-07, Vol.146, p.105567-105567, Article 105567
Hauptverfasser: Azizi, SeyedArmin, Soleimani, Reza, Ahmadi, Mohsen, Malekan, Ali, Abualigah, Laith, Dashtiahangar, Fatemeh
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 105567
container_issue
container_start_page 105567
container_title Computers in biology and medicine
container_volume 146
creator Azizi, SeyedArmin
Soleimani, Reza
Ahmadi, Mohsen
Malekan, Ali
Abualigah, Laith
Dashtiahangar, Fatemeh
description Cardiopulmonary resuscitation refers to the process of sending oxygen and blood to the body's vital organs during cardiac arrest. For this reason, designing and controlling an accurate robot is crucial to saving the lives of patients. This study aims to optimize two nonlinear robust controllers for the first time for the parallel manipulator for cardiopulmonary resuscitation to reduce overshoot, increase accuracy, increase convergence speed, and increase robustness to destructive factors affecting the precision of the robots. The paper first presents the kinematics and dynamics of a translational parallel manipulator robot. Then, to reduce the difference between the practical and simulation results, the paper presents a nonlinear model under uncertainties, disturbances, and noise. Then, the ONSTSMC awaiting the uncertainty band is designed to eliminate the singularity problem and increase the accuracy and robustness to destructive factors, as well as improve stability using the Lyapunov principle. Furthermore, the results of applying this robust controller to the robot are compared with the results of a non-singular terminal sliding mode controller without considering the uncertainty band, a conventional sliding mode controller, and a PID controller for the same model. The developed controller exhibits better performance in terms of accuracy and convergence time even when external and internal destructive factors are present. The accuracy is 0.21 mm and the convergence time is 0.7 seconds when compared with PID. Furthermore, it is approximately 0.17 mm and 0.4 seconds faster compared with conventional sliding mode controllers. •Modification of the model and designing two optimized nonlinear robust controllers.•Design and control of an accurate parallel manipulator medical robot and cardiopulmonary resuscitation.•Increase the accuracy of the position and convergence speed, and robustness to destructive factors affecting the robot's precision.•An ONSTSMC awaiting the uncertainty band eliminates the singularity problem and improves accuracy and robustness.
doi_str_mv 10.1016/j.compbiomed.2022.105567
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2681045411</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0010482522003596</els_id><sourcerecordid>2681045411</sourcerecordid><originalsourceid>FETCH-LOGICAL-c379t-ebe01290c8eee1bd17b7b3eb0343cd3e896f48247e04af3d49ae6ed0b0bfb3c93</originalsourceid><addsrcrecordid>eNqFkU1LBDEMhosouH78h4IXL7Om087XUcUvWNCDnkvbybBdZtq17Sj-e7usIHjxFJI-SfrmJYQyWDJg9dVmafy01dZP2C9LKMtcrqq6OSAL1jZdARUXh2QBwKAQbVkdk5MYNwAggMOCrF8wDD5Myhmk6Na7OKFL1A9UOTrnNCRlHXXejdahCjQvskaNNHjtE_20aU39Ntkpl36h_DjHRI13KfhxxHBGjgY1Rjz_iafk7f7u9faxWD0_PN1erwrDmy4VqBFY2YFpEZHpnjW60Rw1cMFNz7Ht6iHLEA2CUAPvRaewxh406EFz0_FTcrmfuw3-fcaY5GSjwXFUDv0cZVm3DEQlGMvoxR904-fg8u8y1bSsq5sKMtXuKRN8jAEHuQ1ZbPiSDOTOArmRvxbInQVyb0Fuvdm3Yhb8YTHIaCzmk_Y2oEmy9_b_Id9Xnpcv</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2678196750</pqid></control><display><type>article</type><title>Performance enhancement of an uncertain nonlinear medical robot with optimal nonlinear robust controller</title><source>ScienceDirect Journals (5 years ago - present)</source><source>ProQuest Central UK/Ireland</source><creator>Azizi, SeyedArmin ; Soleimani, Reza ; Ahmadi, Mohsen ; Malekan, Ali ; Abualigah, Laith ; Dashtiahangar, Fatemeh</creator><creatorcontrib>Azizi, SeyedArmin ; Soleimani, Reza ; Ahmadi, Mohsen ; Malekan, Ali ; Abualigah, Laith ; Dashtiahangar, Fatemeh</creatorcontrib><description>Cardiopulmonary resuscitation refers to the process of sending oxygen and blood to the body's vital organs during cardiac arrest. For this reason, designing and controlling an accurate robot is crucial to saving the lives of patients. This study aims to optimize two nonlinear robust controllers for the first time for the parallel manipulator for cardiopulmonary resuscitation to reduce overshoot, increase accuracy, increase convergence speed, and increase robustness to destructive factors affecting the precision of the robots. The paper first presents the kinematics and dynamics of a translational parallel manipulator robot. Then, to reduce the difference between the practical and simulation results, the paper presents a nonlinear model under uncertainties, disturbances, and noise. Then, the ONSTSMC awaiting the uncertainty band is designed to eliminate the singularity problem and increase the accuracy and robustness to destructive factors, as well as improve stability using the Lyapunov principle. Furthermore, the results of applying this robust controller to the robot are compared with the results of a non-singular terminal sliding mode controller without considering the uncertainty band, a conventional sliding mode controller, and a PID controller for the same model. The developed controller exhibits better performance in terms of accuracy and convergence time even when external and internal destructive factors are present. The accuracy is 0.21 mm and the convergence time is 0.7 seconds when compared with PID. Furthermore, it is approximately 0.17 mm and 0.4 seconds faster compared with conventional sliding mode controllers. •Modification of the model and designing two optimized nonlinear robust controllers.•Design and control of an accurate parallel manipulator medical robot and cardiopulmonary resuscitation.•Increase the accuracy of the position and convergence speed, and robustness to destructive factors affecting the robot's precision.•An ONSTSMC awaiting the uncertainty band eliminates the singularity problem and improves accuracy and robustness.</description><identifier>ISSN: 0010-4825</identifier><identifier>EISSN: 1879-0534</identifier><identifier>DOI: 10.1016/j.compbiomed.2022.105567</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Accuracy ; Cardiopulmonary resuscitation ; Control algorithms ; Controllers ; Convergence ; CPR ; Design ; Fractures ; Hospitals ; Kinematics ; Manipulators ; Medical robots ; Neural networks ; Nonlinear control ; Optimization ; Organs ; Performance enhancement ; Proportional integral derivative ; Resuscitation ; Robot arms ; Robotics ; Robots ; Robust control ; Sliding mode control ; Uncertainty</subject><ispartof>Computers in biology and medicine, 2022-07, Vol.146, p.105567-105567, Article 105567</ispartof><rights>2022 Elsevier Ltd</rights><rights>2022. Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c379t-ebe01290c8eee1bd17b7b3eb0343cd3e896f48247e04af3d49ae6ed0b0bfb3c93</citedby><cites>FETCH-LOGICAL-c379t-ebe01290c8eee1bd17b7b3eb0343cd3e896f48247e04af3d49ae6ed0b0bfb3c93</cites><orcidid>0000-0003-1550-110X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2678196750?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,3549,27923,27924,45994,64384,64386,64388,72340</link.rule.ids></links><search><creatorcontrib>Azizi, SeyedArmin</creatorcontrib><creatorcontrib>Soleimani, Reza</creatorcontrib><creatorcontrib>Ahmadi, Mohsen</creatorcontrib><creatorcontrib>Malekan, Ali</creatorcontrib><creatorcontrib>Abualigah, Laith</creatorcontrib><creatorcontrib>Dashtiahangar, Fatemeh</creatorcontrib><title>Performance enhancement of an uncertain nonlinear medical robot with optimal nonlinear robust controller</title><title>Computers in biology and medicine</title><description>Cardiopulmonary resuscitation refers to the process of sending oxygen and blood to the body's vital organs during cardiac arrest. For this reason, designing and controlling an accurate robot is crucial to saving the lives of patients. This study aims to optimize two nonlinear robust controllers for the first time for the parallel manipulator for cardiopulmonary resuscitation to reduce overshoot, increase accuracy, increase convergence speed, and increase robustness to destructive factors affecting the precision of the robots. The paper first presents the kinematics and dynamics of a translational parallel manipulator robot. Then, to reduce the difference between the practical and simulation results, the paper presents a nonlinear model under uncertainties, disturbances, and noise. Then, the ONSTSMC awaiting the uncertainty band is designed to eliminate the singularity problem and increase the accuracy and robustness to destructive factors, as well as improve stability using the Lyapunov principle. Furthermore, the results of applying this robust controller to the robot are compared with the results of a non-singular terminal sliding mode controller without considering the uncertainty band, a conventional sliding mode controller, and a PID controller for the same model. The developed controller exhibits better performance in terms of accuracy and convergence time even when external and internal destructive factors are present. The accuracy is 0.21 mm and the convergence time is 0.7 seconds when compared with PID. Furthermore, it is approximately 0.17 mm and 0.4 seconds faster compared with conventional sliding mode controllers. •Modification of the model and designing two optimized nonlinear robust controllers.•Design and control of an accurate parallel manipulator medical robot and cardiopulmonary resuscitation.•Increase the accuracy of the position and convergence speed, and robustness to destructive factors affecting the robot's precision.•An ONSTSMC awaiting the uncertainty band eliminates the singularity problem and improves accuracy and robustness.</description><subject>Accuracy</subject><subject>Cardiopulmonary resuscitation</subject><subject>Control algorithms</subject><subject>Controllers</subject><subject>Convergence</subject><subject>CPR</subject><subject>Design</subject><subject>Fractures</subject><subject>Hospitals</subject><subject>Kinematics</subject><subject>Manipulators</subject><subject>Medical robots</subject><subject>Neural networks</subject><subject>Nonlinear control</subject><subject>Optimization</subject><subject>Organs</subject><subject>Performance enhancement</subject><subject>Proportional integral derivative</subject><subject>Resuscitation</subject><subject>Robot arms</subject><subject>Robotics</subject><subject>Robots</subject><subject>Robust control</subject><subject>Sliding mode control</subject><subject>Uncertainty</subject><issn>0010-4825</issn><issn>1879-0534</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkU1LBDEMhosouH78h4IXL7Om087XUcUvWNCDnkvbybBdZtq17Sj-e7usIHjxFJI-SfrmJYQyWDJg9dVmafy01dZP2C9LKMtcrqq6OSAL1jZdARUXh2QBwKAQbVkdk5MYNwAggMOCrF8wDD5Myhmk6Na7OKFL1A9UOTrnNCRlHXXejdahCjQvskaNNHjtE_20aU39Ntkpl36h_DjHRI13KfhxxHBGjgY1Rjz_iafk7f7u9faxWD0_PN1erwrDmy4VqBFY2YFpEZHpnjW60Rw1cMFNz7Ht6iHLEA2CUAPvRaewxh406EFz0_FTcrmfuw3-fcaY5GSjwXFUDv0cZVm3DEQlGMvoxR904-fg8u8y1bSsq5sKMtXuKRN8jAEHuQ1ZbPiSDOTOArmRvxbInQVyb0Fuvdm3Yhb8YTHIaCzmk_Y2oEmy9_b_Id9Xnpcv</recordid><startdate>202207</startdate><enddate>202207</enddate><creator>Azizi, SeyedArmin</creator><creator>Soleimani, Reza</creator><creator>Ahmadi, Mohsen</creator><creator>Malekan, Ali</creator><creator>Abualigah, Laith</creator><creator>Dashtiahangar, Fatemeh</creator><general>Elsevier Ltd</general><general>Elsevier Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M7P</scope><scope>M7Z</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-1550-110X</orcidid></search><sort><creationdate>202207</creationdate><title>Performance enhancement of an uncertain nonlinear medical robot with optimal nonlinear robust controller</title><author>Azizi, SeyedArmin ; Soleimani, Reza ; Ahmadi, Mohsen ; Malekan, Ali ; Abualigah, Laith ; Dashtiahangar, Fatemeh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c379t-ebe01290c8eee1bd17b7b3eb0343cd3e896f48247e04af3d49ae6ed0b0bfb3c93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Accuracy</topic><topic>Cardiopulmonary resuscitation</topic><topic>Control algorithms</topic><topic>Controllers</topic><topic>Convergence</topic><topic>CPR</topic><topic>Design</topic><topic>Fractures</topic><topic>Hospitals</topic><topic>Kinematics</topic><topic>Manipulators</topic><topic>Medical robots</topic><topic>Neural networks</topic><topic>Nonlinear control</topic><topic>Optimization</topic><topic>Organs</topic><topic>Performance enhancement</topic><topic>Proportional integral derivative</topic><topic>Resuscitation</topic><topic>Robot arms</topic><topic>Robotics</topic><topic>Robots</topic><topic>Robust control</topic><topic>Sliding mode control</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Azizi, SeyedArmin</creatorcontrib><creatorcontrib>Soleimani, Reza</creatorcontrib><creatorcontrib>Ahmadi, Mohsen</creatorcontrib><creatorcontrib>Malekan, Ali</creatorcontrib><creatorcontrib>Abualigah, Laith</creatorcontrib><creatorcontrib>Dashtiahangar, Fatemeh</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Computing Database</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Biochemistry Abstracts 1</collection><collection>Research Library (Corporate)</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Computers in biology and medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Azizi, SeyedArmin</au><au>Soleimani, Reza</au><au>Ahmadi, Mohsen</au><au>Malekan, Ali</au><au>Abualigah, Laith</au><au>Dashtiahangar, Fatemeh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Performance enhancement of an uncertain nonlinear medical robot with optimal nonlinear robust controller</atitle><jtitle>Computers in biology and medicine</jtitle><date>2022-07</date><risdate>2022</risdate><volume>146</volume><spage>105567</spage><epage>105567</epage><pages>105567-105567</pages><artnum>105567</artnum><issn>0010-4825</issn><eissn>1879-0534</eissn><abstract>Cardiopulmonary resuscitation refers to the process of sending oxygen and blood to the body's vital organs during cardiac arrest. For this reason, designing and controlling an accurate robot is crucial to saving the lives of patients. This study aims to optimize two nonlinear robust controllers for the first time for the parallel manipulator for cardiopulmonary resuscitation to reduce overshoot, increase accuracy, increase convergence speed, and increase robustness to destructive factors affecting the precision of the robots. The paper first presents the kinematics and dynamics of a translational parallel manipulator robot. Then, to reduce the difference between the practical and simulation results, the paper presents a nonlinear model under uncertainties, disturbances, and noise. Then, the ONSTSMC awaiting the uncertainty band is designed to eliminate the singularity problem and increase the accuracy and robustness to destructive factors, as well as improve stability using the Lyapunov principle. Furthermore, the results of applying this robust controller to the robot are compared with the results of a non-singular terminal sliding mode controller without considering the uncertainty band, a conventional sliding mode controller, and a PID controller for the same model. The developed controller exhibits better performance in terms of accuracy and convergence time even when external and internal destructive factors are present. The accuracy is 0.21 mm and the convergence time is 0.7 seconds when compared with PID. Furthermore, it is approximately 0.17 mm and 0.4 seconds faster compared with conventional sliding mode controllers. •Modification of the model and designing two optimized nonlinear robust controllers.•Design and control of an accurate parallel manipulator medical robot and cardiopulmonary resuscitation.•Increase the accuracy of the position and convergence speed, and robustness to destructive factors affecting the robot's precision.•An ONSTSMC awaiting the uncertainty band eliminates the singularity problem and improves accuracy and robustness.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.compbiomed.2022.105567</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-1550-110X</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0010-4825
ispartof Computers in biology and medicine, 2022-07, Vol.146, p.105567-105567, Article 105567
issn 0010-4825
1879-0534
language eng
recordid cdi_proquest_miscellaneous_2681045411
source ScienceDirect Journals (5 years ago - present); ProQuest Central UK/Ireland
subjects Accuracy
Cardiopulmonary resuscitation
Control algorithms
Controllers
Convergence
CPR
Design
Fractures
Hospitals
Kinematics
Manipulators
Medical robots
Neural networks
Nonlinear control
Optimization
Organs
Performance enhancement
Proportional integral derivative
Resuscitation
Robot arms
Robotics
Robots
Robust control
Sliding mode control
Uncertainty
title Performance enhancement of an uncertain nonlinear medical robot with optimal nonlinear robust controller
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T22%3A28%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Performance%20enhancement%20of%20an%20uncertain%20nonlinear%20medical%20robot%20with%20optimal%20nonlinear%20robust%20controller&rft.jtitle=Computers%20in%20biology%20and%20medicine&rft.au=Azizi,%20SeyedArmin&rft.date=2022-07&rft.volume=146&rft.spage=105567&rft.epage=105567&rft.pages=105567-105567&rft.artnum=105567&rft.issn=0010-4825&rft.eissn=1879-0534&rft_id=info:doi/10.1016/j.compbiomed.2022.105567&rft_dat=%3Cproquest_cross%3E2681045411%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2678196750&rft_id=info:pmid/&rft_els_id=S0010482522003596&rfr_iscdi=true