{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T17:06:16Z","timestamp":1776359176845,"version":"3.51.2"},"reference-count":36,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Advanced Engineering Informatics"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.aei.2026.104672","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T13:05:28Z","timestamp":1776344728000},"page":"104672","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["A meta-learning-guided TD3 control algorithm with adaptive experience replay for active vibration isolator"],"prefix":"10.1016","volume":"74","author":[{"given":"Weipeng","family":"Li","sequence":"first","affiliation":[]},{"given":"Haohui","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xiaoguang","family":"Ren","sequence":"additional","affiliation":[]},{"given":"Zeshu","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Cui","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"6","key":"10.1016\/j.aei.2026.104672_b1","article-title":"Modified acceleration feedback for active vibration control of aerospace structures","volume":"19","author":"Mahmoodi","year":"2010","journal-title":"Smart Mater. Struct."},{"issue":"6","key":"10.1016\/j.aei.2026.104672_b2","doi-asserted-by":"crossref","first-page":"4619","DOI":"10.1109\/TVT.2015.2437455","article-title":"Filter-based adaptive vibration control for active vehicle suspensions with electrohydraulic actuators","volume":"65","author":"Sun","year":"2015","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"1","key":"10.1016\/j.aei.2026.104672_b3","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1080\/15376494.2012.677103","article-title":"Vibration control on smart civil structures: A review","volume":"21","author":"Amezquita-Sanchez","year":"2014","journal-title":"Mech. Adv. Mater. Struct."},{"issue":"2","key":"10.1016\/j.aei.2026.104672_b4","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.arcontrol.2013.09.012","article-title":"Advances in modeling and vibration control of building structures","volume":"37","author":"Thenozhi","year":"2013","journal-title":"Annu. Rev. Control."},{"key":"10.1016\/j.aei.2026.104672_b5","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/j.actaastro.2018.03.023","article-title":"Experiments study on attitude coupling control method for flexible spacecraft","volume":"147","author":"Wang","year":"2018","journal-title":"Acta Astronaut."},{"issue":"1","key":"10.1016\/j.aei.2026.104672_b6","first-page":"82","article-title":"Analysis of stick-slip reduction for a new torsional vibration tool based on PID control","volume":"234","author":"Tian","year":"2020","journal-title":"Proc. Inst. Mech. Eng. Part K: J. Multi-Body Dyn."},{"issue":"4","key":"10.1016\/j.aei.2026.104672_b7","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1177\/1461348419852454","article-title":"Active vibration control of a horizontal flexible plate structure using intelligent proportional\u2013integral\u2013derivative controller tuned by fuzzy logic and artificial bee colony algorithm","volume":"39","author":"Hadi","year":"2020","journal-title":"J. Low Freq. Noise, Vib. Act. Control."},{"key":"10.1016\/j.aei.2026.104672_b8","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.engstruct.2014.09.042","article-title":"Stability analysis of active vibration control of building structures using PD\/PID control","volume":"81","author":"Thenozhi","year":"2014","journal-title":"Eng. Struct."},{"issue":"6","key":"10.1016\/j.aei.2026.104672_b9","doi-asserted-by":"crossref","first-page":"2443","DOI":"10.2514\/1.J056510","article-title":"Nonprobabilistic reliable LQR design method for active vibration control of structures with uncertainties","volume":"56","author":"Li","year":"2018","journal-title":"AIAA J."},{"key":"10.1016\/j.aei.2026.104672_b10","article-title":"Fuzzy PID control of nonlinear vibration isolator with parallel electromagnetic negative stiffness","volume":"vol. 2170","author":"Xie","year":"2022"},{"key":"10.1016\/j.aei.2026.104672_b11","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.procs.2022.01.020","article-title":"Iterative feedback tuning algorithm for tower crane systems","volume":"199","author":"Roman","year":"2022","journal-title":"Procedia Comput. Sci."},{"issue":"9","key":"10.1016\/j.aei.2026.104672_b12","doi-asserted-by":"crossref","first-page":"3461","DOI":"10.1109\/TIE.2008.925322","article-title":"Fuzzy control system performance enhancement by iterative learning control","volume":"55","author":"Precup","year":"2008","journal-title":"IEEE Trans. Ind. Electron."},{"issue":"4","key":"10.1016\/j.aei.2026.104672_b13","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1016\/j.engappai.2004.11.003","article-title":"Adaptive fuzzy sliding mode control for flexible satellite","volume":"18","author":"Guan","year":"2005","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.aei.2026.104672_b14","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.engappai.2017.07.005","article-title":"Particle swarm optimization for generating interpretable fuzzy reinforcement learning policies","volume":"65","author":"Hein","year":"2017","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"2","key":"10.1016\/j.aei.2026.104672_b15","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1109\/TIV.2020.3012947","article-title":"Comparison of deep reinforcement learning and model predictive control for adaptive cruise control","volume":"6","author":"Lin","year":"2020","journal-title":"IEEE Trans. Intell. Veh."},{"key":"10.1016\/j.aei.2026.104672_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.120495","article-title":"Reinforcement learning algorithms: A brief survey","volume":"231","author":"Shakya","year":"2023","journal-title":"Expert Syst. Appl."},{"issue":"18","key":"10.1016\/j.aei.2026.104672_b17","doi-asserted-by":"crossref","first-page":"7827","DOI":"10.3390\/s23187827","article-title":"Research on deep reinforcement learning control algorithm for active suspension considering uncertain time delay","volume":"23","author":"Wang","year":"2023","journal-title":"Sensors"},{"issue":"2","key":"10.1016\/j.aei.2026.104672_b18","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1007\/s10489-018-1296-x","article-title":"Applications of asynchronous deep reinforcement learning based on dynamic updating weights","volume":"49","author":"Zhao","year":"2019","journal-title":"Appl. Intell."},{"issue":"5","key":"10.1016\/j.aei.2026.104672_b19","doi-asserted-by":"crossref","DOI":"10.1088\/1361-665X\/abee35","article-title":"Design of model-free reinforcement learning control for tunable vibration absorber system based on magnetorheological elastomer","volume":"30","author":"Park","year":"2021","journal-title":"Smart Mater. Struct."},{"issue":"4","key":"10.1016\/j.aei.2026.104672_b20","doi-asserted-by":"crossref","first-page":"5064","DOI":"10.1109\/TNNLS.2022.3207346","article-title":"Deep reinforcement learning: A survey","volume":"35","author":"Wang","year":"2022","journal-title":"IEEE Trans. Neural Networks Learn. Syst."},{"issue":"18","key":"10.1016\/j.aei.2026.104672_b21","doi-asserted-by":"crossref","first-page":"3925","DOI":"10.3390\/electronics12183925","article-title":"Multi-phase focused pid adaptive tuning with reinforcement learning","volume":"12","author":"Ding","year":"2023","journal-title":"Electronics"},{"issue":"8","key":"10.1016\/j.aei.2026.104672_b22","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1111\/mice.12934","article-title":"A hierarchical framework for improving ride comfort of autonomous vehicles via deep reinforcement learning with external knowledge","volume":"38","author":"Du","year":"2023","journal-title":"Computer-Aided Civ. Infrastruct. Eng."},{"issue":"2","key":"10.1016\/j.aei.2026.104672_b23","article-title":"Intelligent control of structural vibrations based on deep reinforcement learning","volume":"4","author":"Guo","year":"2025","journal-title":"J. Infrastruct. Intell. Resil."},{"key":"10.1016\/j.aei.2026.104672_b24","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2025.113029","article-title":"Active vibration control of magnetically coupled piezoelectric flexible hinged plate using batch-constrained deep Q-learning reinforcement learning","volume":"236","author":"Qiu","year":"2025","journal-title":"Mech. Syst. Signal Process."},{"issue":"11","key":"10.1016\/j.aei.2026.104672_b25","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2024.e32167","article-title":"Path planning of mobile robot based on improved TD3 algorithm in dynamic environment","volume":"10","author":"Li","year":"2024","journal-title":"Heliyon"},{"key":"10.1016\/j.aei.2026.104672_b26","doi-asserted-by":"crossref","first-page":"38017","DOI":"10.1109\/ACCESS.2024.3375083","article-title":"UAV path planning based on the average TD3 algorithm with prioritized experience replay","volume":"12","author":"Luo","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.aei.2026.104672_b27","article-title":"Hierarchical TD3 reinforcement learning with stackelberg game and attention mechanism for safe and efficient autonomous lane-changing","author":"Yu","year":"2025","journal-title":"IEEE Access"},{"key":"10.1016\/j.aei.2026.104672_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.ast.2022.107801","article-title":"Reinforcement learning vibration control of a multi-flexible beam coupling system","volume":"129","author":"Qiu","year":"2022","journal-title":"Aerosp. Sci. Technol."},{"key":"10.1016\/j.aei.2026.104672_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.109108","article-title":"An immune optimization deep reinforcement learning control method used for magnetorheological elastomer vibration absorber","volume":"137","author":"Wang","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.aei.2026.104672_b30","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2023.102328","article-title":"Enhancing vehicle ride comfort through deep reinforcement learning with expert-guided soft-hard constraints and system characteristic considerations","volume":"59","author":"Wang","year":"2024","journal-title":"Adv. Eng. Inform."},{"issue":"1","key":"10.1016\/j.aei.2026.104672_b31","doi-asserted-by":"crossref","first-page":"18331","DOI":"10.1038\/s41598-025-02244-z","article-title":"Efficient TD3 based path planning of mobile robot in dynamic environments using prioritized experience replay and LSTM","volume":"15","author":"Lin","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.aei.2026.104672_b32","series-title":"2024 5th International Conference on Artificial Intelligence and Electromechanical Automation","first-page":"934","article-title":"TD3 with composite forgetting prioritized experience replay","author":"Wang","year":"2024"},{"issue":"9","key":"10.1016\/j.aei.2026.104672_b33","first-page":"5149","article-title":"Meta-learning in neural networks: A survey","volume":"44","author":"Hospedales","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"23","key":"10.1016\/j.aei.2026.104672_b34","doi-asserted-by":"crossref","first-page":"10821","DOI":"10.3390\/app142310821","article-title":"Adaptive position control of pneumatic continuum manipulator based on MAML meta-reinforcement learning","volume":"14","author":"Hao","year":"2024","journal-title":"Appl. Sci."},{"key":"10.1016\/j.aei.2026.104672_b35","series-title":"International Conference on Machine Learning","first-page":"1587","article-title":"Addressing function approximation error in actor-critic methods","author":"Fujimoto","year":"2018"},{"key":"10.1016\/j.aei.2026.104672_b36","doi-asserted-by":"crossref","first-page":"101552","DOI":"10.1109\/ACCESS.2019.2930567","article-title":"General theory of skyhook control and its application to semi-active suspension control strategy design","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Access"}],"container-title":["Advanced Engineering Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626003642?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626003642?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T16:17:54Z","timestamp":1776356274000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1474034626003642"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":36,"alternative-id":["S1474034626003642"],"URL":"https:\/\/doi.org\/10.1016\/j.aei.2026.104672","relation":{},"ISSN":["1474-0346"],"issn-type":[{"value":"1474-0346","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A meta-learning-guided TD3 control algorithm with adaptive experience replay for active vibration isolator","name":"articletitle","label":"Article Title"},{"value":"Advanced Engineering Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aei.2026.104672","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104672"}}