Cisneros, Pablo S. G.Pablo S. G.CisnerosSridharan, AadithyanAadithyanSridharanWerner, HerbertHerbertWerner2019-04-252019-04-252018-11-23IFAC-PapersOnLine 26 (51): 118-123 (2018)http://hdl.handle.net/11420/2481In 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.en2405-8963201826118123Elsevierhttps://creativecommons.org/licenses/by-nc-nd/4.0/TechnikIngenieurwissenschaftenJournal Article10.15480/882.347210.1016/j.ifacol.2018.11.15810.15480/882.3472Other