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The TSMC is designed for a second-order mathematical model of RWBR. Then robust adaptive dynamic programming based on an actor-critic algorithm is used to optimise the TSMC only by data sampled online. The system closed-loop stability and convergence of the neural network weights are guaranteed based on the Lyapunov analysis. The effectiveness of the proposed algorithm is demonstrated through simulations and experiments.<\/jats:p>","DOI":"10.1017\/s0263574724001437","type":"journal-article","created":{"date-parts":[[2024,12,19]],"date-time":"2024-12-19T12:33:12Z","timestamp":1734611592000},"page":"3416-3430","source":"Crossref","is-referenced-by-count":3,"title":["Online robust self-learning terminal sliding mode control for balancing control of reaction wheel bicycle robots"],"prefix":"10.1017","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8894-5700","authenticated-orcid":false,"given":"Xianjin","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenfu","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Deng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyuan","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2024,12,19]]},"reference":[{"key":"S0263574724001437_ref34","volume-title":"Reinforcement Learning: An Introduction","author":"Sutton RS","year":"2018"},{"key":"S0263574724001437_ref9","first-page":"173","article-title":"LQR and MPC controller design and comparison for a stationary self-balancing bicycle robot with a reaction wheel","volume":"51","author":"Kanjanawanishkul","year":"2015","journal-title":"Kybernetika"},{"key":"S0263574724001437_ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3268524"},{"key":"S0263574724001437_ref19","doi-asserted-by":"publisher","DOI":"10.1049\/csy2.12032"},{"key":"S0263574724001437_ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2020.3042876"},{"key":"S0263574724001437_ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.isatra.2023.11.032"},{"key":"S0263574724001437_ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMECH.2020.2998506"},{"key":"S0263574724001437_ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9340949"},{"key":"S0263574724001437_ref3","doi-asserted-by":"publisher","DOI":"10.1017\/S026357471400112X"},{"key":"S0263574724001437_ref24","doi-asserted-by":"crossref","unstructured":"[24] Huo, B. , Yu, L. , Liu, Y. and Sha, S. , \u201cReinforcement learning based path tracking control method for unmanned bicycle on complex terrain,\u201d In: IECON. 2023- 49th Annual Conference of the IEEE Industrial Electronics Society, Singapore, Singapore (2023) pp. 1\u20136.","DOI":"10.1109\/IECON51785.2023.10312041"},{"key":"S0263574724001437_ref5","doi-asserted-by":"crossref","unstructured":"[5] Beznos, A. , Formal\u2019sky, A. , Gurfinkel, E. , Jicharev, D. , Lensky, A. , Savitsky, K. and Tchesalin, L. , \u201cControl of autonomous motion of two-wheel bicycle with gyroscopic stabilisation,\u201d In: IEEE International Conference on Robotics and Automation, Leuven, Belgium,\u00a0(1998) pp. 2670\u20132675.","DOI":"10.1109\/ROBOT.1998.680749"},{"key":"S0263574724001437_ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2022.105064"},{"key":"S0263574724001437_ref12","doi-asserted-by":"crossref","unstructured":"[12] Xiong, C. , Huang, Z. , Gu, W. , Pan, Q. , Liu, Y. , Li, X. and Wang, E. 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