{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T05:31:42Z","timestamp":1774416702666,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,11,26]],"date-time":"2023-11-26T00:00:00Z","timestamp":1700956800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>This research introduces a robust control design for multibody robot systems, incorporating sliding mode control (SMC) for robustness against uncertainties and disturbances. SMC achieves this through directing system states toward a predefined sliding surface for finite-time stability. However, the challenge arises in selecting controller parameters, specifically the switching gain, as it depends on the upper bounds of perturbations, including nonlinearities, uncertainties, and disturbances, impacting the system. Consequently, gain selection becomes challenging when system dynamics are unknown. To address this issue, an extended state observer (ESO) is integrated with SMC, resulting in SMCESO, which treats system dynamics and disturbances as perturbations and estimates them to compensate for their effects on the system response, ensuring robust performance. To further enhance system performance, deep deterministic policy gradient (DDPG) is employed to fine-tune SMCESO, utilizing both actual and estimated states as input states for the DDPG agent and reward selection. This training process enhances both tracking and estimation performance. Furthermore, the proposed method is compared with the optimal-PID, SMC, and H\u221e in the presence of external disturbances and parameter variation. MATLAB\/Simulink simulations confirm that overall, the SMCESO provides robust performance, especially with parameter variations, where other controllers struggle to converge the tracking error to zero.<\/jats:p>","DOI":"10.3390\/robotics12060161","type":"journal-article","created":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T03:32:03Z","timestamp":1701055923000},"page":"161","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["DDPG-Based Adaptive Sliding Mode Control with Extended State Observer for Multibody Robot Systems"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6851-8231","authenticated-orcid":false,"given":"Hamza","family":"Khan","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Pusan National University, Busan 46241, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9594-1457","authenticated-orcid":false,"given":"Sheraz Ali","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Mechatronics Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4472-1267","authenticated-orcid":false,"given":"Min Cheol","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Pusan National University, Busan 46241, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5464-4002","authenticated-orcid":false,"given":"Usman","family":"Ghafoor","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Pusan National University, Busan 46241, Republic of Korea"},{"name":"Department of Mechanical Engineering, Institute of Space Technology, Islamabad 44000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9354-7982","authenticated-orcid":false,"given":"Fouzia","family":"Gillani","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering & Technology, Government College University, Faisalabad 37000, Pakistan"}]},{"given":"Umer Hameed","family":"Shah","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering and Artificial Intelligence Research Center, College of Engineering and Information Technology, Ajman University, Ajman P.O. Box 346, United Arab Emirates"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Shtessel, Y., Edwards, C., Fridman, L., and Levant, A. (2014). Sliding Mode Control and Observation, Birkh\u00e4user. Control Engineering.","DOI":"10.1007\/978-0-8176-4893-0"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Afifa, R., Ali, S., Pervaiz, M., and Iqbal, J. (2023). Adaptive Backstepping Integral Sliding Mode Control of a MIMO Separately Excited Dc Motor. 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