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Syst."],"published-print":{"date-parts":[[2022,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>For motion control of uncertain servomechanisms, nonlinear dynamics including smooth and nonsmooth types, external disturbances, signal measurement noises, asymmetric input saturation, and so on seriously hinder the further development of high-performance closed-loop control algorithms. However, already existing control strategies cannot address the above-mentioned issues at the same time. It greatly increases the difficulty of controller design especially when some states are not measurable. Inspired by above motivations, this paper exploits neural networks to deal with nonlinear dynamics including discontinuous types, and combines extended state observers to estimate disturbances and unmeasurable states for uncertain nonlinear servomechanisms. Meanwhile, the desired-command-based model compensation approach is integrated into the controller design. It is worth noting that the neural network weights are updated by the combination of the estimation error and tracking error to acquire better approximation accuracy. According to above technologies, a novel extended-state-observer-based neural network adaptive motion control algorithm will be synthesized. The bounded stability of the whole closed-loop system is proved strictly. In addition, the comparisons of the application results on an electro-hydraulic servo system verify the availability and superiority of the developed control algorithm.<\/jats:p>","DOI":"10.1007\/s40747-022-00643-7","type":"journal-article","created":{"date-parts":[[2022,2,11]],"date-time":"2022-02-11T09:03:22Z","timestamp":1644570202000},"page":"2527-2539","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Neuroadaptive control of information-poor servomechanisms with smooth and nonsmooth uncertainties"],"prefix":"10.1007","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4164-7700","authenticated-orcid":false,"given":"Guichao","family":"Yang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2052-0452","authenticated-orcid":false,"given":"Hua","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,2,11]]},"reference":[{"issue":"2","key":"643_CR1","doi-asserted-by":"publisher","first-page":"1171","DOI":"10.1109\/TIE.2011.2162217","volume":"59","author":"H Liu","year":"2012","unstructured":"Liu H, Li S (2012) Speed control for PMSM servo system using predictive functional control and extended state observer. 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This work was supported in part by the National Natural Science Foundation of China under Grant 52005249, in part by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant 20KJB460019 and in part by the Key Research & Development Program of Jiangsu Province under Grant BE2019007-3.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}