{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T04:34:34Z","timestamp":1777437274895,"version":"3.51.4"},"reference-count":26,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Advanced Robotic Systems"],"published-print":{"date-parts":[[2014,3,1]]},"abstract":"<jats:p>Real-time balance control of an eight-link biped robot using a zero moment point (ZMP) dynamic model is difficult to achieve due to the processing time of the corresponding equations. To overcome this limitation an intelligent computing technique based on Support Vector Regression (SVR) is developed and presented in this paper. To implement a PD controller the SVR uses the ZMP error relative to a reference and its variation as inputs, and the output is the correction of the angle of the robot's torso, necessary for its sagittal balance. The SVR was trained based on simulation data generated using a PD controller. The initial values of the parameters of the PD controller were obtained by the second Ziegler-Nichols method. In order to evaluate the balance performance of the biped robot, three performance indexes are used.<\/jats:p>\n                  <jats:p>The ZMP is calculated by reading four force sensors placed under each of the robot's feet. The gait implemented in this biped is similar to a human gait, which is acquired and adapted to the robot's size.<\/jats:p>\n                  <jats:p>The main contribution of this paper is the fine-tuning of the ZMP controller based on the SVR. To implement and test this, the biped robot was subjected to external forces and slope variation. Some experiments are presented and the results show that the implemented gait combined with the correct tuning of the SVR controller is appropriate for use with this biped robot. The SVR controller runs at 0.2 ms, which is about 50 times faster than a corresponding first-order TSK neural-fuzzy network.<\/jats:p>","DOI":"10.5772\/57526","type":"journal-article","created":{"date-parts":[[2014,3,10]],"date-time":"2014-03-10T06:13:40Z","timestamp":1394432020000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Tuning a PD Controller Based on an SVR for the Control of a Biped Robot Subject to External Forces and Slope Variation"],"prefix":"10.1177","volume":"11","author":[{"given":"Jo\u00e3o P.","family":"Ferreira","sequence":"first","affiliation":[{"name":"Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, Portugal"},{"name":"Department of Electrical Engineering, Superior Institute of Engineering of Coimbra, Coimbra, Portugal"}]},{"given":"Manuel","family":"Cris\u00f3stomo","sequence":"additional","affiliation":[{"name":"Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, Portugal"}]},{"given":"A. Paulo","family":"Coimbra","sequence":"additional","affiliation":[{"name":"Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, Portugal"}]}],"member":"179","published-online":{"date-parts":[[2014,1,1]]},"reference":[{"key":"bibr1-57526","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-83006-8"},{"key":"bibr2-57526","doi-asserted-by":"publisher","DOI":"10.1109\/ICSMC.2004.1398398"},{"key":"bibr3-57526","unstructured":"Yoo J.H., Nixon M. S., Harris C. J. \u201cExtracting Human Gait Signatures by Body Segment Properties\u201d, Fifth IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI.02), pp. 35\u201339."},{"key":"bibr4-57526","doi-asserted-by":"publisher","DOI":"10.1109\/WISP.2007.4447537"},{"key":"bibr5-57526","unstructured":"Winter D. A. \u201cThe Biomechanics and Motor Control of Human Movement\u201d, 2nd Ed. John Wiley & Sons, 1990, pp.73\u201396."},{"key":"bibr6-57526","doi-asserted-by":"crossref","unstructured":"Hirai K., Hirose M., Haikawa Y, Takenaka T. \u201cThe Development of Honda Humanoid Robot\u201d, Proc. Int. Conf. Robotics and Automation, pp. 1321\u20131326, 1998.","DOI":"10.1109\/ROBOT.1998.677288"},{"key":"bibr7-57526","unstructured":"Ferreira J. P., Cris\u00f3stomo Manuel, Coimbra A. P., Ribeiro B. \u201cSVR Controller for a Biped Robot with a Human-like Gait Subjected to External Sagittal Forces\u201d, Biped Robots, InTech Publisher, ISBN: 978\u2013953\u2013307\u2013216\u20136, 2011, pp. 77\u201398."},{"key":"bibr8-57526","first-page":"1231","volume-title":"Proceedings of the 2006 IEEE International Conference on Robotics and Automation","author":"Park I.W.","year":"2006"},{"key":"bibr9-57526","doi-asserted-by":"publisher","DOI":"10.1163\/156855307780132063"},{"key":"bibr10-57526","doi-asserted-by":"crossref","unstructured":"Prahlad V., Dip G., Hwee C. M. \u201cDisturbance rejection by online ZMP compensation\u201d, Robotica, pp. 1\u20139, 2007.","DOI":"10.1017\/S0263574707003542"},{"key":"bibr11-57526","doi-asserted-by":"crossref","unstructured":"Low K. H., Liu X., Goh C. H., Yu H. \u201cLocomotive Control of a Wearable Lower Exoskeleton for Walking Enhancement\u201d, Journal of Vibration and Control, 2006, pp. 1311\u20131336.","DOI":"10.1177\/1077546306070616"},{"key":"bibr12-57526","first-page":"253","volume-title":"Proceedings of the 10th International Symposium on Robotics with Applications","author":"Ferreira J. P.","year":"2004"},{"key":"bibr13-57526","doi-asserted-by":"publisher","DOI":"10.1049\/ip-cta:20045007"},{"key":"bibr14-57526","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2006.1641935"},{"key":"bibr15-57526","first-page":"117","volume-title":"Proceedings of the 16th IFAC World Congress","author":"Kati\u0107 D.","year":"2006"},{"key":"bibr16-57526","volume-title":"\u201cThe Nature of Statistical Learning Theory\u201d","author":"Vapnik V.","year":"1998"},{"key":"bibr17-57526","doi-asserted-by":"publisher","DOI":"10.1109\/WISP.2007.4447538"},{"key":"bibr18-57526","first-page":"51","volume-title":"IEEE Seventh International Conference on Intelligent Engineering Systems","author":"Mohamed R. M.","year":"2003"},{"key":"bibr19-57526","first-page":"659","volume":"12","author":"Vapnik V.","year":"1999","journal-title":"\u201c;Support Vector Method for Multivariate Density Estimation, Advances in Neural Information Processing Systems\u201d"},{"key":"bibr20-57526","doi-asserted-by":"crossref","unstructured":"Chang C.C., Lin C.J. \u201cLIBSVM: a Library for Support Vector Machines\u201d, January 2 2007.","DOI":"10.1145\/1961189.1961199"},{"key":"bibr21-57526","doi-asserted-by":"crossref","unstructured":"Ziegler J. G., Nichols N. B. \u201cOptimum settings for automatic controllers,\u201d Trans. ASME, vol. 64, pp. 759\u2013768, Nov. 1942.","DOI":"10.1115\/1.4019264"},{"issue":"9","key":"bibr22-57526","doi-asserted-by":"crossref","first-page":"2979","DOI":"10.1109\/TIM.2009.2016801","volume":"58","author":"Jo\u00e3o","year":"2009","journal-title":"IEEE Transaction on Instrument and Measurement"},{"key":"bibr23-57526","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574706003031"},{"key":"bibr24-57526","doi-asserted-by":"publisher","DOI":"10.1142\/S0219843604000083"},{"key":"bibr25-57526","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1985.6313399"},{"key":"bibr26-57526","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2009.2032183"}],"container-title":["International Journal of Advanced Robotic Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.5772\/57526","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.5772\/57526","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.5772\/57526","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T12:01:32Z","timestamp":1777377692000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.5772\/57526"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,1,1]]},"references-count":26,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2014,3,1]]}},"alternative-id":["10.5772\/57526"],"URL":"https:\/\/doi.org\/10.5772\/57526","relation":{},"ISSN":["1729-8806","1729-8814"],"issn-type":[{"value":"1729-8806","type":"print"},{"value":"1729-8814","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,1,1]]},"article-number":"32"}}