{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T12:46:23Z","timestamp":1774010783954,"version":"3.50.1"},"reference-count":29,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100031935","name":"Xi&apos;an Jiaotong University","doi-asserted-by":"publisher","award":["HMHAI-202402"],"award-info":[{"award-number":["HMHAI-202402"]}],"id":[{"id":"10.13039\/100031935","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62573397"],"award-info":[{"award-number":["62573397"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62573398"],"award-info":[{"award-number":["62573398"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.neucom.2026.132773","type":"journal-article","created":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T17:03:46Z","timestamp":1769101426000},"page":"132773","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Online safe tracking control with barrier-like functions: Coordinating dynamic output performance and obstacle avoidance"],"prefix":"10.1016","volume":"674","author":[{"given":"Ambreen","family":"Basheer","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Man","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiming","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahu","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2026.132773_bib0005","first-page":"435","article-title":"An overview of prescribed performance control and its application to spacecraft attitude system","volume":"235","author":"Wei","year":"2020","journal-title":"Proc. Inst. Mech. Eng. Part I J. Syst. Control Eng."},{"key":"10.1016\/j.neucom.2026.132773_bib0010","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1002\/asjc.2765","article-title":"Prescribed performance control approaches, applications and challenges: a comprehensive survey","volume":"25","author":"Bu","year":"2022","journal-title":"Asian J. Control"},{"issue":"4","key":"10.1016\/j.neucom.2026.132773_bib0015","doi-asserted-by":"crossref","first-page":"918","DOI":"10.1016\/j.automatica.2008.11.017","article-title":"Barrier lyapunov functions for the control of output-constrained nonlinear systems","volume":"45","author":"Tee","year":"2009","journal-title":"Automatica"},{"key":"10.1016\/j.neucom.2026.132773_bib0020","doi-asserted-by":"crossref","first-page":"9709","DOI":"10.1016\/j.jfranklin.2020.07.037","article-title":"Asymmetric integral barrier lyapunov function-based adaptive tracking control considering full-state with input magnitude and rate constraint","volume":"357","author":"Liu","year":"2020","journal-title":"J. Frankl. Inst."},{"issue":"1","key":"10.1016\/j.neucom.2026.132773_bib0025","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.ifacol.2018.05.002","article-title":"Barrier lyapunov function based state-constrained control for a class of nonlinear systems","volume":"51","author":"Sachan","year":"2018","journal-title":"IFAC-PapersOnLine"},{"issue":"20","key":"10.1016\/j.neucom.2026.132773_bib0030","doi-asserted-by":"crossref","first-page":"449","DOI":"10.3182\/20130902-3-CN-3020.00122","article-title":"Tangent barrier lyapunov functions for the control of output-constrained nonlinear systems","volume":"46","author":"Tang","year":"2013","journal-title":"IFAC Proc. Vol."},{"key":"10.1016\/j.neucom.2026.132773_bib0035","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.neucom.2015.12.075","article-title":"Adaptive control of nonlinear systems with full state constraints using integral barrier lyapunov functionals","volume":"186","author":"Li","year":"2016","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.132773_bib0040","doi-asserted-by":"crossref","first-page":"3316","DOI":"10.1016\/j.jfranklin.2019.12.017","article-title":"Online barrier-actor-critic learning forH\u221econtrol with full-state constraints and input saturation","volume":"357","author":"Yang","year":"2020","journal-title":"J. Frankl. Inst."},{"key":"10.1016\/j.neucom.2026.132773_bib0045","series-title":"2021 American Control Conference (ACC)","first-page":"1979","article-title":"A safety aware model-based reinforcement learning framework for systems with uncertainties","author":"Mahmud","year":"2021"},{"issue":"5","key":"10.1016\/j.neucom.2026.132773_bib0050","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1080\/00207179.2019.1639825","article-title":"TABLF-based adaptive control for uncertain nonlinear systems with time-varying asymmetric full-state constraints","volume":"94","author":"Wang","year":"2021","journal-title":"Int. J. Control"},{"key":"10.1016\/j.neucom.2026.132773_bib0055","article-title":"Full-state time-varying asymmetric constraint control for non-strict feedback nonlinear systems based on dynamic surface method","volume":"12","author":"Yang","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.neucom.2026.132773_bib0060","doi-asserted-by":"crossref","DOI":"10.1049\/iet-cta.2020.0165","article-title":"Full state constraints control of switched complex networks based on time-varying barrier lyapunov functions","volume":"14","author":"Enchang","year":"2020","journal-title":"IET Control Theory Appl."},{"key":"10.1016\/j.neucom.2026.132773_bib0065","series-title":"2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","first-page":"8129","article-title":"Comparative analysis of control barrier functions and artificial potential fields for obstacle avoidance","author":"Singletary","year":"2021"},{"key":"10.1016\/j.neucom.2026.132773_bib0070","series-title":"2017 IEEE 56th Annual Conference on Decision and Control (CDC)","first-page":"2242","article-title":"Hamilton-jacobi reachability: a brief overview and recent advances","author":"Bansal","year":"2017"},{"key":"10.1016\/j.neucom.2026.132773_bib0075","series-title":"2015 54th IEEE Conference on Decision and Control (CDC)","first-page":"650","article-title":"Approximate optimal online continuous-time path-planner with static obstacle avoidance","author":"Walters","year":"2015"},{"key":"10.1016\/j.neucom.2026.132773_bib0080","series-title":"2020 59th IEEE Conference on Decision and Control (CDC)","first-page":"2062","article-title":"Approximate optimal control for safety-critical systems with control barrier functions","author":"Cohen","year":"2020"},{"key":"10.1016\/j.neucom.2026.132773_bib0085","article-title":"Safe reinforcement learning and adaptive optimal control with applications to obstacle avoidance problem","author":"Wang","year":"2023","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"10.1016\/j.neucom.2026.132773_bib0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.automatica.2022.110684","article-title":"Safe exploration in model-based reinforcement learning using control barrier functions","volume":"147","author":"Cohen","year":"2023","journal-title":"Automatica"},{"issue":"5","key":"10.1016\/j.neucom.2026.132773_bib0095","doi-asserted-by":"crossref","first-page":"2079","DOI":"10.1109\/TAI.2023.3325780","article-title":"Safe adaptive dynamic programming for multiplayer systems with static and moving no-entry regions","volume":"5","author":"Mu","year":"2024","journal-title":"IEEE Trans. Artif. Intell."},{"issue":"2","key":"10.1016\/j.neucom.2026.132773_bib0100","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1109\/TRO.2019.2955321","article-title":"Approximate optimal motion planning to avoid unknown moving avoidance regions","volume":"36","author":"Deptula","year":"2019","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.neucom.2026.132773_bib0105","series-title":"2019 18th European Control Conference (ECC)","first-page":"3420","article-title":"Control barrier functions: theory and applications","author":"Ames","year":"2019"},{"issue":"16","key":"10.1016\/j.neucom.2026.132773_bib0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.jfranklin.2025.108037","article-title":"Approximate optimal trajectory tracking and dynamic obstacle avoidance for affine system via online learning","volume":"362","author":"Basheer","year":"2025","journal-title":"J. Frankl. Inst."},{"key":"10.1016\/j.neucom.2026.132773_bib0115","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.automatica.2016.08.004","article-title":"Efficient model-based reinforcement learning for approximate online optimal control","volume":"74","author":"Kamalapurkar","year":"2016","journal-title":"Automatica"},{"key":"10.1016\/j.neucom.2026.132773_bib0120","series-title":"Nonlinear Control of Engineering Systems: A Lyapunov-Based Approach","author":"Dixon","year":"2003"},{"key":"10.1016\/j.neucom.2026.132773_bib0125","series-title":"Robust Adaptive Control","volume":"vol. 1","author":"Ioannou","year":"1996"},{"key":"10.1016\/j.neucom.2026.132773_bib0130","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.automatica.2014.10.103","article-title":"Approximate optimal trajectory tracking for continuous-time nonlinear systems","volume":"51","author":"Kamalapurkar","year":"2015","journal-title":"Automatica"},{"key":"10.1016\/j.neucom.2026.132773_bib0135","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.automatica.2015.10.039","article-title":"Model-based reinforcement learning for approximate optimal regulation","volume":"64","author":"Kamalapurkar","year":"2016","journal-title":"Automatica"},{"key":"10.1016\/j.neucom.2026.132773_bib0140","doi-asserted-by":"crossref","DOI":"10.1016\/j.automatica.2020.108922","article-title":"Data-based reinforcement learning approximate optimal control for an uncertain nonlinear system with control effectiveness faults","volume":"116","author":"Deptula","year":"2020","journal-title":"Automatica"},{"key":"10.1016\/j.neucom.2026.132773_bib0145","series-title":"Control of Nonlinear Systems","author":"Khalil","year":"2002"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226001700?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226001700?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T10:41:09Z","timestamp":1774003269000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226001700"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":29,"alternative-id":["S0925231226001700"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.132773","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Online safe tracking control with barrier-like functions: Coordinating dynamic output performance and obstacle avoidance","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.132773","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"132773"}}