{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T09:17:32Z","timestamp":1758273452343,"version":"3.41.2"},"reference-count":18,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T00:00:00Z","timestamp":1610409600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJICC"],"published-print":{"date-parts":[[2021,1,12]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to apply a intelligent algorithm to conduct the force tracking control for electrohydraulic servo system (EHSS). Specifically, the adaptive neuro-fuzzy inference system (ANFIS) is selected to improve the control performance for EHSS.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Two types of input\u2013output data were chosen to train the ANFIS models. The inputs are the desired and actual forces, and the output is the current. The first type is to set a sinusoidal signal for the current to produce the actual driving force, and the desired force is chosen as same as the actual force. The other type is to give a sinusoidal signal for the desired force. Under the action of the PI controller, the actual force tracks the desired force, and the current is the output of the PI controller.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The models built based on the two types of data are separately named as the ANFIS I controller and the ANFIS II controller. The results reveal that the ANFIS I controller possesses the best performance in terms of overshoot, rise time and mean absolute error and show adaptivity to different tracking conditions, including sinusoidal signal tracking and sudden change signal tracking.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This paper is the first time to apply the ANFIS to optimize the force tracking control for EHSS.<\/jats:p><\/jats:sec>","DOI":"10.1108\/ijicc-09-2020-0132","type":"journal-article","created":{"date-parts":[[2021,1,13]],"date-time":"2021-01-13T05:10:44Z","timestamp":1610514644000},"page":"1-16","source":"Crossref","is-referenced-by-count":3,"title":["Force tracking control for electrohydraulic servo system based on adaptive neuro-fuzzy inference system (ANFIS) controller"],"prefix":"10.1108","volume":"14","author":[{"given":"Lie","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fangli","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianbin","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yukang","family":"Tian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"first-page":"2502","article-title":"Fuzzy PID controller design using Q-learning algorithm with a manipulated reward function","year":"2017","key":"key2021030404134031200_ref001"},{"key":"key2021030404134031200_ref002","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.mechmachtheory.2017.07.018","article-title":"Dynamic modeling of a 2-d of parallel electrohydraulic actuated homokinetic platform","volume":"118","year":"2017","journal-title":"Mechanism and Machine Theory"},{"key":"key2021030404134031200_ref003","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.isatra.2019.06.018","article-title":"An electrohydraulic load sensing system based on flow\/pressure switched control for mobile machinery","volume":"96","year":"2020","journal-title":"ISA Transactions"},{"issue":"10","key":"key2021030404134031200_ref004","first-page":"1499","article-title":"Control DC motor speed with adaptive neuro-fuzzy control (ANFIS)","volume":"5","year":"2011","journal-title":"Australian Journal of Basic and Applied Sciences"},{"key":"key2021030404134031200_ref005","doi-asserted-by":"crossref","first-page":"125638","DOI":"10.1109\/ACCESS.2020.3007615","article-title":"Speed control of direct current motor using ANFIS based hybrid PID configuration controller","volume":"8","year":"2020","journal-title":"IEEE Access"},{"issue":"4","key":"key2021030404134031200_ref006","doi-asserted-by":"crossref","first-page":"1092","DOI":"10.1109\/TCST.2011.2158101","article-title":"Feedback linearization based position control of an electrohydraulic servo system with supply pressure uncertainty","volume":"20","year":"2012","journal-title":"IEEE Transactions on Control Systems Technology"},{"key":"key2021030404134031200_ref007","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1109\/TMECH.2006.886190","article-title":"Identification and real-time control of an electrohydraulic servo system based on nonlinear backstepping","volume":"12","year":"2007","journal-title":"IEEE\/ASME Transactions on Mechatronics"},{"key":"key2021030404134031200_ref008","doi-asserted-by":"crossref","first-page":"12951","DOI":"10.1109\/ACCESS.2017.2723541","article-title":"Comparison of an ANFIS and fuzzy PID control model for performance in a two-axis inertial stabilized platform","volume":"5","year":"2017","journal-title":"IEEE Access"},{"volume-title":"Hydraulic Control Systems","year":"1967","key":"key2021030404134031200_ref009"},{"issue":"7","key":"key2021030404134031200_ref010","doi-asserted-by":"crossref","first-page":"3907","DOI":"10.1016\/j.jfranklin.2019.12.042","article-title":"Constrained neural adaptive PID control for robot manipulators","volume":"357","year":"2020","journal-title":"Journal of the Franklin Institute"},{"issue":"1","key":"key2021030404134031200_ref011","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1108\/IJICC-09-2016-0034","article-title":"Chaos control of the power system via sliding mode based on fuzzy supervisor","volume":"10","year":"2017","journal-title":"International Journal of Intelligent Computing and Cybernetics"},{"issue":"3","key":"key2021030404134031200_ref012","first-page":"1437","article-title":"Adaptive neuro-fuzzy inference system (ANFIS) based direct torque control of PMSM driven centrifugal pump","volume":"7","year":"2017","journal-title":"International Journal of Renewable Energy Resources"},{"key":"key2021030404134031200_ref013","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.neucom.2020.03.063","article-title":"Adaptive neuro-fuzzy PID controller based on twin delayed deep deterministic policy gradient algorithm","volume":"402","year":"2020","journal-title":"Neurocomputing"},{"issue":"5","key":"key2021030404134031200_ref014","first-page":"4169","article-title":"Development and repetitive learning control of lower limb exoskeleton driven by electro-hydraulic actuators","volume":"64","year":"2016","journal-title":"IEEE Transactions on Industrial Electronics"},{"issue":"1","key":"key2021030404134031200_ref015","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1109\/TMECH.2017.2746142","article-title":"Position tracking control law for an electro-hydraulic servo system based on backstepping and extended differentiator","volume":"23","year":"2018","journal-title":"IEEE\/ASME Transactions on Mechatronics"},{"issue":"6","key":"key2021030404134031200_ref016","doi-asserted-by":"crossref","first-page":"954","DOI":"10.1016\/S1000-9361(11)60467-6","article-title":"Robust control for static loading of electro-hydraulic load simulator with friction compensation","volume":"25","year":"2012","journal-title":"Chinese Journal of Aeronautics"},{"issue":"3","key":"key2021030404134031200_ref017","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1016\/j.cja.2013.04.001","article-title":"Friction compensation for low velocity control of hydraulic flight motion simulator: a simple adaptive robust approach","volume":"26","year":"2013","journal-title":"Chinese Journal of Aeronautics"},{"issue":"3","key":"key2021030404134031200_ref018","first-page":"944","article-title":"Active disturbance rejection control of position control for electrohydraulic servo system","volume":"28","year":"2020","journal-title":"Engineering Letters"}],"container-title":["International Journal of Intelligent Computing and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJICC-09-2020-0132\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJICC-09-2020-0132\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T22:54:54Z","timestamp":1753397694000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/ijicc\/article\/14\/1\/1-16\/125008"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,12]]},"references-count":18,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1,12]]}},"alternative-id":["10.1108\/IJICC-09-2020-0132"],"URL":"https:\/\/doi.org\/10.1108\/ijicc-09-2020-0132","relation":{},"ISSN":["1756-378X"],"issn-type":[{"type":"print","value":"1756-378X"}],"subject":[],"published":{"date-parts":[[2021,1,12]]}}}