|Publisher DOI:||10.1016/j.ifacol.2018.11.158||Title:||Constrained Predictive Control of a Robotic Manipulator using quasi-LPV Representations||Language:||English||Authors:||Cisneros, P. S.G.
|Issue Date:||2018||Source:||IFAC-PapersOnLine 26 (51): 118-123 (2018)||Journal or Series Name:||IFAC-PapersOnLine||Abstract (english):||In this paper a practical approach to Nonlinear Model Predictive Control (NMPC) of a robotic manipulator subject to nonlinear state constraints is presented, which leads to a successful experimental implementation of the control algorithm. The use of quasi-LPV modelling is at the core of this scheme as complex nonlinear optimization is replaced by efficient Quadratic Programming (QP) exploiting the quasi-linearity of the resulting model and constraints. The quasi-LPV model is obtained via velocity-based linearization which results in an exact representation of the nonlinear dynamics and enables stability guarantees with offset-free control. The experimental results show the efficiency and efficacy of the algorithm, as well as its robustness to unmodelled dynamics.||URI:||http://hdl.handle.net/11420/2481||ISSN:||2405-8963||Institute:||Regelungstechnik E-14||Type:||(wissenschaftlicher) Artikel|
|Appears in Collections:||Publications without fulltext|
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