{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T12:14:45Z","timestamp":1780402485221,"version":"3.54.1"},"reference-count":27,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.engappai.2026.114994","type":"journal-article","created":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T17:50:04Z","timestamp":1777571404000},"page":"114994","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P2","title":["Reinforcement learning-based hybrid force\/position control of redundant manipulators under time delays"],"prefix":"10.1016","volume":"177","author":[{"given":"Mojtaba","family":"Radan Kashani","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1922-4488","authenticated-orcid":false,"given":"Maryam","family":"Malekzadeh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Allireza","family":"Ariaei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"58","key":"10.1016\/j.engappai.2026.114994_b1","doi-asserted-by":"crossref","DOI":"10.1126\/scirobotics.abf2756","article-title":"A cerebellar-based solution to the nondeterministic time delay problem in robotic control","volume":"6","author":"Abad\u00eda","year":"2021","journal-title":"Sci. Robot."},{"key":"10.1016\/j.engappai.2026.114994_b2","series-title":"2022 American Control Conference","first-page":"2722","article-title":"A reinforcement learning-based adaptive time-delay control and its application to robot manipulators","author":"Baek","year":"2022"},{"issue":"3","key":"10.1016\/j.engappai.2026.114994_b3","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/s11768-020-9061-1","article-title":"Adaptive high-order sliding mode control based on quasi-time delay estimation for uncertain robot manipulator","volume":"18","author":"Brahmi","year":"2020","journal-title":"Control. Theory Technol."},{"issue":"7","key":"10.1016\/j.engappai.2026.114994_b4","doi-asserted-by":"crossref","first-page":"4844","DOI":"10.1002\/rnc.7236","article-title":"Reinforcement learning-based event-triggered optimal control for unknown nonlinear systems with input delay","volume":"34","author":"Chen","year":"2024","journal-title":"Internat. J. Robust Nonlinear Control"},{"issue":"2","key":"10.1016\/j.engappai.2026.114994_b5","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1002\/acs.3706","article-title":"Improved sliding mode observer based repetitive control for linear systems with time-varying input and state delays","volume":"38","author":"Chuei","year":"2024","journal-title":"Internat. J. Adapt. Control Signal Process."},{"key":"10.1016\/j.engappai.2026.114994_b6","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.engappai.2026.114994_b7","doi-asserted-by":"crossref","first-page":"128096","DOI":"10.1109\/ACCESS.2020.3008152","article-title":"Robust adaptive sliding-mode control of a permanent magnetic spherical actuator with delay compensation","volume":"8","author":"Guo","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.114994_b8","series-title":"International Conference on Machine Learning","first-page":"1861","article-title":"Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor","author":"Haarnoja","year":"2018"},{"key":"10.1016\/j.engappai.2026.114994_b9","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.106052","article-title":"Modeling and control of wastewater treatment process with time delay based on event-triggered recursive least squares","volume":"122","author":"Han","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.114994_b10","first-page":"1","article-title":"Effective hybrid force\/position control of robots using reinforcement learning","author":"Kashani","year":"2025","journal-title":"Int. J. Syst. Sci."},{"issue":"3","key":"10.1016\/j.engappai.2026.114994_b11","doi-asserted-by":"crossref","first-page":"214","DOI":"10.5302\/J.ICROS.2024.23.0097","article-title":"Experimental studies on hybrid force control with sliding mode configuration for a robot manipulator","volume":"30","author":"Lee","year":"2024","journal-title":"J. Inst. Control. Robot. Syst."},{"key":"10.1016\/j.engappai.2026.114994_b12","series-title":"Continuous control with deep reinforcement learning","author":"Lillicrap","year":"2015"},{"key":"10.1016\/j.engappai.2026.114994_b13","doi-asserted-by":"crossref","DOI":"10.1016\/j.conengprac.2026.107016","article-title":"CLOE-inspired control for autonomous systems with noisy feedback and unknown dynamics","volume":"173","author":"Malekizadeh","year":"2026","journal-title":"Control Eng. Pract."},{"key":"10.1016\/j.engappai.2026.114994_b14","series-title":"2005 IEEE\/RSJ International Conference on Intelligent Robots and Systems","first-page":"3901","article-title":"Comparative experiments on task space control with redundancy resolution","author":"Nakanishi","year":"2005"},{"issue":"4","key":"10.1016\/j.engappai.2026.114994_b15","doi-asserted-by":"crossref","first-page":"2462","DOI":"10.3390\/app13042462","article-title":"Intelligent time delay control of telepresence robots using novel deep reinforcement learning algorithm to interact with patients","volume":"13","author":"Naseer","year":"2023","journal-title":"Appl. Sci."},{"key":"10.1016\/j.engappai.2026.114994_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.107174","article-title":"Gaussian process regression for forward and inverse kinematics of a soft robotic arm","volume":"126","author":"Rela\u00f1o","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.114994_b17","unstructured":"Robotis, , (2025). OpenMANIPULATOR-X specification. ROBOTIS e-Manual. Retrieved August, 31, 2025 from https:\/\/emanual.robotis.com\/docs\/en\/platform\/openmanipulator_x."},{"key":"10.1016\/j.engappai.2026.114994_b18","series-title":"Robotics: Modelling, Planning and Control","author":"Siciliano","year":"2009"},{"key":"10.1016\/j.engappai.2026.114994_b19","series-title":"Reinforcement Learning: An Introduction","author":"Sutton","year":"2018"},{"issue":"7","key":"10.1016\/j.engappai.2026.114994_b20","doi-asserted-by":"crossref","DOI":"10.3390\/robotics13070105","article-title":"ANN enhanced hybrid force\/position controller of robot manipulators for fiber placement","volume":"13","author":"Villa-Tiburcio","year":"2024","journal-title":"Robotics"},{"key":"10.1016\/j.engappai.2026.114994_b21","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.engappai.2026.114994_b22","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.109610","article-title":"Transformer-based partner dance motion generation","volume":"139","author":"Wu","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.114994_b23","doi-asserted-by":"crossref","first-page":"127048","DOI":"10.1109\/ACCESS.2020.3008399","article-title":"A new reinforcement learning based adaptive sliding mode control scheme for free-floating space robotic manipulator","volume":"8","author":"Xie","year":"2020","journal-title":"IEEE Access"},{"issue":"8","key":"10.1016\/j.engappai.2026.114994_b24","doi-asserted-by":"crossref","first-page":"10368","DOI":"10.1109\/TNNLS.2023.3241070","article-title":"Sliding mode control based on reinforcement learning for TS fuzzy fractional-order multiagent system with time-varying delays","volume":"35","author":"Yan","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.engappai.2026.114994_b25","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.110231","article-title":"A learning-based algorithm for turn-based orbital pursuit-evasion problem with reaction-time delay","volume":"145","author":"Zhao","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.114994_b26","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.113609","article-title":"Efficient surrogate-based optimization framework integrating physics-informed neural networks, deep active learning and deep reinforcement learning: Multilayer thin films case study","volume":"166","author":"Zheng","year":"2026","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"3","key":"10.1016\/j.engappai.2026.114994_b27","doi-asserted-by":"crossref","DOI":"10.1177\/1729881420916276","article-title":"Trajectory tracking sliding mode control for underactuated autonomous underwater vehicles with time delays","volume":"17","author":"Zhou","year":"2020","journal-title":"Int. J. Adv. Robot. Syst."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626012777?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626012777?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T11:59:00Z","timestamp":1780401540000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626012777"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":27,"alternative-id":["S0952197626012777"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114994","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Reinforcement learning-based hybrid force\/position control of redundant manipulators under time delays","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114994","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":"114994"}}