{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:23:52Z","timestamp":1754155432671,"version":"3.41.2"},"reference-count":25,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2013,8,16]],"date-time":"2013-08-16T00:00:00Z","timestamp":1376611200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,8,16]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The paper aims to overcome the shortcomings that proportional\u2010integral\u2010derivative (PID) control for unmanned robot applied to automotive test (URAT) needs a priori manual retuning, has large speed fluctuations and is hard to adjust control parameters. A novel control approach based on fuzzy neural network applied to URAT was proposed.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>According to the target vehicle speed and driving command table, the multiple manipulator coordinated control model was established. After that, the displacement of throttle mechanical leg, clutch mechanical leg, brake mechanical leg and shift mechanical arm for URAT was used as input of fuzzy neural network (FNN) model, and vehicle speed was used as output of FNN model. The number of membership functions was three, and the type of that was generalized bell membership function (gbellmf). The hybrid learning algorithm which combined with back propagation algorithm and least square method was applied to train the model. The Sugeno model was selected as fuzzy reasoning model.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>Experimental results demonstrated that compared with PID control method, the proposed approach can greatly improve the accuracy of vehicle speed tracking. The approach can accurately realize the vehicle speed tracking of given driving test cycle. Therefore, it can ensure the accuracy and effectiveness of automotive test results.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>Future work will focus on improving the efficiency of this learning algorithm.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>The paper provides effective methods for improving the accuracy of speed tracking and repeatability.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>After establishing the multiple manipulator coordinated control model, this paper proposes a novel control approach based on FNN for URAT.<\/jats:p><\/jats:sec>","DOI":"10.1108\/ir-08-2012-398","type":"journal-article","created":{"date-parts":[[2013,8,14]],"date-time":"2013-08-14T11:36:15Z","timestamp":1376480175000},"page":"450-461","source":"Crossref","is-referenced-by-count":12,"title":["Fuzzy neural control for unmanned robot applied to automotive test"],"prefix":"10.1108","volume":"40","author":[{"given":"Gang","family":"Chen","sequence":"first","affiliation":[]},{"given":"Wei\u2010gong","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Xiao\u2010na","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2022012920220152600_b18","unstructured":"Brandstetter, P. and Skotnica, M. (2011), \u201cANN speed controller for induction motor drive with vector control\u201d, International Review of Electrical Engineering (IREE\u2009), Vol. 6 No. 7, pp. 2947\u20102954."},{"key":"key2022012920220152600_b13","unstructured":"Chambers, C., Stol, K. and Halkyard, R. (2008), \u201cAutonomous vehicle following using a robotic driver\u201d, Mechatronics and Machine Vision in Practice in 2008 Proceedings of the 15th International Conference in Auckland, New Zealand, pp. 115\u2010120."},{"key":"key2022012920220152600_b25","doi-asserted-by":"crossref","unstructured":"Chen, G. and Zhang, W.G. (2013), \u201cSpeed tracking control of a vehicle robot driver system using multiple sliding surface control schemes\u201d, International Journal of Advanced Robotic Systems, Vol. 10 (in press).","DOI":"10.5772\/53750"},{"key":"key2022012920220152600_b20","unstructured":"Chen, G., Zhang, W.G. and Chang, S.Q. (2011), \u201cShift control method of vehicle robot driver based on fuzzy neural network\u201d, Transactions of Chinese Society for Agricultural Machinery, Vol. 42 No. 6, pp. 6\u201011."},{"key":"key2022012920220152600_b22","unstructured":"Chen, G., Zhang, W.G., Gong, Z.Y., Sun, W. and Zhao, M.Q. (2009), \u201cCoordinated control of multiple manipulators for vehicle robot driver\u201d, Chinese Journal of Scientific Instrument, Vol. 30 No. 9, pp. 1836\u20101840."},{"key":"key2022012920220152600_b2","unstructured":"Chen, X.B. and Zhang, W.G. (2005), \u201cRobot driver for vehicle durability emission test on chassis dynamometer\u201d, Journal of Southeast University, Vol. 21 No. 7, pp. 33\u201038 (English Edition)."},{"key":"key2022012920220152600_b9","unstructured":"Chen, X.B., Zhang, W.G. and Zhang, B.J. (2005), \u201cStudy on speed tracking control strategy for robot driver on chassis dynamometer\u201d, China Mechanical Engineering, Vol. 16 No. 18, pp. 1669\u20101673."},{"key":"key2022012920220152600_b24","doi-asserted-by":"crossref","unstructured":"Chun, F.H. and Bore, K.L. (2011), \u201cFPGA\u2010based adaptive PID control of a DC motor driver via sliding\u2010mode approach\u201d, Expert System with Applications, Vol. 38, pp. 11866\u201011872.","DOI":"10.1016\/j.eswa.2011.02.185"},{"key":"key2022012920220152600_b17","doi-asserted-by":"crossref","unstructured":"Fritz, H. (1996), \u201cNeural speed control for autonomous road vehicles\u201d, Control Engineering Practice, Vol. 4 No. 4, pp. 507\u2010512.","DOI":"10.1016\/0967-0661(96)00033-0"},{"key":"key2022012920220152600_b15","unstructured":"Horishi, T. (1998), \u201cAutomatic speed control device using self\u2010tuning fuzzy logic\u201d, Automotive Applications of Electronics in 1998 Proceedings of the IEEE Workshop in Piscataway, USA, pp. 65\u201071."},{"key":"key2022012920220152600_b19","doi-asserted-by":"crossref","unstructured":"Jang, R. (1993), \u201cANFIS: adaptive network\u2010based fuzzy inference systems\u201d, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 23 No. 3, pp. 665\u2010685.","DOI":"10.1109\/21.256541"},{"key":"key2022012920220152600_b8","unstructured":"Muller, K. and Leonhard, W. (1992), \u201cComputer control of a robotic driver for emission tests\u201d, Industrial Electronics, Control, Instrumentation, and Automation in 1992 Proceedings of the International Conference in San Diego, America, pp. 1506\u20101511."},{"key":"key2022012920220152600_b11","unstructured":"Namik, H., Inamura, T. and Stol, K. (2006), \u201cDevelopment of a robotic driver for vehicle dynamometer testing\u201d, Robotics and Automation in 2006 Proceedings of the Australasian Conference in Auckland, New Zealand, pp. 1\u20109."},{"key":"key2022012920220152600_b14","doi-asserted-by":"crossref","unstructured":"Nejad, F.B. and Azadi, S. (1998), \u201cVehicle velocity control using fuzzy self\u2010tuning method\u201d, Vehicle System Dynamics, Vol. 29 No. 5, pp. 331\u2010338.","DOI":"10.1080\/00423119808969378"},{"key":"key2022012920220152600_b10","unstructured":"Sailer, S., Buchholz, M. and Dietmayer, K. (2001), \u201cFlatness based velocity tracking control of a vehicle on a roller dynamometer using a robotic driver\u201d, Decision and Control in 2001 Proceedings of the 50th IEEE Conference and European Control Conference in Orlando, FL, USA, pp. 7962\u20107967."},{"key":"key2022012920220152600_b1","doi-asserted-by":"crossref","unstructured":"Samuel, S., Austin, L. and Morrey, D. (2002), \u201cAutomotive test drive cycles for emission measurement and real\u2010world emission levels \u2013 a review\u201d, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 216 No. 7, pp. 555\u2010564.","DOI":"10.1243\/095440702760178587"},{"key":"key2022012920220152600_b5","unstructured":"Schwarze, K., Gollinger, H. and Busch, A. (1998), \u201cActuator concepts for an autonomous robotic driver\u201d, Intelligent Vehicles in 1998 Proceedings of the IEEE International Conference in Stuttgart, Germany, pp. 463\u2010468."},{"key":"key2022012920220152600_b6","unstructured":"Shoval, S., Zyburt, J.P. and Grimaudo, D.W. (1998), \u201cRobot driver for guidance of automatic durability road test vehicles\u201d, Robotics and Automation in 1998 Proceedings of IEEE International Conference in Leuven, Belgium, pp. 1767\u20101772."},{"key":"key2022012920220152600_b3","unstructured":"Spencer, M., Jones, D., Kraehling, M. and Stol, K. (2009), \u201cTrajectory based autonomous vehicle following using a robotic driver\u201d, Robotics and Automation in 2009 Proceedings of the Australasian Conference in Sydney, Australia, 2007, pp. 1\u201010."},{"key":"key2022012920220152600_b23","unstructured":"State Environmental Protection Administration of China (2005), GB 18352.3\u20102005 Limits and Measurement Methods for Emissions from Light\u2010Duty Vehicle (III, IV\u2009), Standards Press of China, Beijing."},{"key":"key2022012920220152600_b4","doi-asserted-by":"crossref","unstructured":"Thiel, W., Gr\u00f6f, S., Hohenberg, G. and Lenzen, B. (1998), \u201cInvestigations on robot driver for vehicle exhaust emission measurements in comparison to the driving strategies of human drivers\u201d, SAE Technical Paper No. 982642, pp. 1922\u20101929.","DOI":"10.4271\/982642"},{"key":"key2022012920220152600_b16","doi-asserted-by":"crossref","unstructured":"Uddin, M.N. and Rahman, M.A. (2007), \u201cHigh\u2010speed control of IPMSM drives using improved fuzzy logic algorithms\u201d, IEEE Transactions on Industrial Electronics, Vol. 54 No. 1, pp. 190\u2010199.","DOI":"10.1109\/TIE.2006.888781"},{"key":"key2022012920220152600_b21","doi-asserted-by":"crossref","unstructured":"Wang, C.H. and Wen, J.S. (2008), \u201cOn the equivalence of a table lookup (TL) technique and fuzzy neural network (FNN) with block pulse membership functions (BPMFs) and its application to water injection control of an automobile\u201d, IEEE Transactions on Systems Man and Cybernetics Part C \u2013 Applications and Reviews, Vol. 38 No. 4, pp. 574\u2010580.","DOI":"10.1109\/TSMCC.2008.923869"},{"key":"key2022012920220152600_b12","doi-asserted-by":"crossref","unstructured":"Wong, N., Chambers, C., Stol, K. and Halkyard, R. (2010), \u201cDevelopment of a robotic driver for autonomous vehicle following\u201d, International Journal of Intelligent Systems Technologies and Applications, Vol. 8 Nos 1\u20104, pp. 276\u2010287.","DOI":"10.1504\/IJISTA.2010.030205"},{"key":"key2022012920220152600_b7","unstructured":"Zhang, W.G. and Chen, X.B. (2005), \u201cKey technologies of vehicle robot driver\u201d, Journal of Jiangsu University, Vol. 26 No. 1, pp. 20\u201023 (Natural Science Edition)."}],"container-title":["Industrial Robot: An International Journal"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.emeraldinsight.com\/doi\/full-xml\/10.1108\/IR-08-2012-398","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IR-08-2012-398\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IR-08-2012-398\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T21:39:38Z","timestamp":1753393178000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/ir\/article\/40\/5\/450-461\/181330"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,8,16]]},"references-count":25,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2013,8,16]]}},"alternative-id":["10.1108\/IR-08-2012-398"],"URL":"https:\/\/doi.org\/10.1108\/ir-08-2012-398","relation":{},"ISSN":["0143-991X"],"issn-type":[{"type":"print","value":"0143-991X"}],"subject":[],"published":{"date-parts":[[2013,8,16]]}}}