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    Constrained predictive control of a robotic manipulator using quasi-LPV representations
    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.
    Publicationtype: Journal Article
    Scopus© Citations 27  206  352
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    Item type:Publication, Access status: with files ,
    LPV control of a gyroscope with inverted pendulum attachment
    A linear parameter varying (LPV) optimal L2 gain controller is designed with mixed-sensitivity shaping to stabilize an inverted pendulum attached to a control moment gyroscope (CMG). Swing-up of the pendulum is achieved by a start-up LPV controller for which the reference is designed by an energy regulator. The LPV performance controller is enabled as soon as the pendulum enters into its operating range of ±0.15 rad. Based on both simulation and experimental results, it is demonstrated that stabilization of the pendulum is achieved for varying gimbal angles and rotational speed of the flywheel.
    Publicationtype: Journal Article
    Scopus© Citations 3  263  337