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A control scheme combined with admittance adaptation and adaptive dynamic programming (ADP) is developed. The unknown environment is modelled as a linear system and admittance controller is derived to achieve compliant behaviour of the robot. In the ADP framework, the cost function is defined with non-quadratic form and the critic network is designed with radial basis function neural network which introduces to obtain an approximate optimal control of the Hamilton\u2013Jacobi\u2013Bellman equation, which guarantees the optimal trajectory tracking. The system stability is analysed by Lyapunov theorem and simulations demonstrate the effectiveness of the proposed strategy.<\/jats:p>","DOI":"10.1007\/s41315-020-00159-8","type":"journal-article","created":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T15:59:48Z","timestamp":1612281588000},"page":"89-100","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Adaptive dynamic programming enhanced admittance control for robots with environment interaction and actuator saturation"],"prefix":"10.1007","volume":"5","author":[{"given":"Hong","family":"Zhan","sequence":"first","affiliation":[]},{"given":"Dianye","family":"Huang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5255-5559","authenticated-orcid":false,"given":"Chenguang","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,2,2]]},"reference":[{"issue":"5","key":"159_CR1","doi-asserted-by":"publisher","first-page":"779","DOI":"10.1016\/j.automatica.2004.11.034","volume":"41","author":"M Abu-Khalaf","year":"2005","unstructured":"Abu-Khalaf, M., Lewis, F.L.: Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network hjb approach. 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