Adaptive Iterative Learning Control for Discrete-Time Nonlinear Systems without Knowing the Control Gain Signs

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Yu, Miao
dc.contributor.author Jämsä-Jounela, Sirkka-Liisa
dc.date.accessioned 2016-09-02T07:48:32Z
dc.date.issued 2013
dc.identifier.citation Yu , M & Jämsä-Jounela , S-L 2013 , Adaptive Iterative Learning Control for Discrete-Time Nonlinear Systems without Knowing the Control Gain Signs . in 18th Nordic Process Control Workshop, Oulu, Finland, 22-23 August, 2013 . en
dc.identifier.other PURE UUID: 21fa5f82-b3df-4fbe-887c-55531ce85bca
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/adaptive-iterative-learning-control-for-discretetime-nonlinear-systems-without-knowing-the-control-gain-signs(21fa5f82-b3df-4fbe-887c-55531ce85bca).html
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/5477829/Adaptive_Iterative_Learning_Control_for_Discrete_Time_Nonlinear_Systems.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/21765
dc.description.abstract An adaptive iterative learning control method is proposed for a class of nonlinear strict-feedback discrete-time systems with random initial conditions and iteration-varying desired trajectories. An n-step ahead predictor approach is employed to estimate the future states in the control design. Discrete Nussbaum gain method is utilized to deal with the lack of a priori knowledge of control directions. The proposed control algorithm guarantees the boundedness of all the signals in the controlled system. The tracking error converges to zero asymptotically along the iterative learning axis except for beginning states affected by random initial conditions. The effectiveness of the proposed control scheme is verified through numerical simulation. en
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries 18th Nordic Process Control Workshop, Oulu, Finland, 22-23 August, 2013 en
dc.rights openAccess en
dc.subject.other 215 Chemical engineering en
dc.subject.other 220 Industrial biotechnology en
dc.subject.other 216 Materials engineering en
dc.title Adaptive Iterative Learning Control for Discrete-Time Nonlinear Systems without Knowing the Control Gain Signs en
dc.type A4 Artikkeli konferenssijulkaisussa fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Biotechnology and Chemical Technology en
dc.contributor.department Department of Chemical and Metallurgical Engineering en
dc.subject.keyword iterative learning control
dc.subject.keyword unknown control directions
dc.subject.keyword discrete Nussbaum gain
dc.subject.keyword n-step ahead state predictor
dc.subject.keyword 215 Chemical engineering
dc.subject.keyword 220 Industrial biotechnology
dc.subject.keyword 216 Materials engineering
dc.identifier.urn URN:NBN:fi:aalto-201609023234
dc.type.version acceptedVersion


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