… to obtain optimal results while satisfying hard constraints and closed-loop robustness in the
… , the predictive control problem for MIMO nonlinear parametrically uncertain systems under …

… of 20 Hz was selected, obeying the Shannon-Nyquist sampling theorem and coping with
the sampling frequency used with the robotic system shown in a similar work of Wang. …

… In this article, we present a model predictive control (MPC) [12] approach that solves the
output regulation problem and does \textit{not} require any offline design such as, eg, solving …

… an alternative to model predictive control (MPC) for unknown nonlinear systems in low-…
presented datadriven control policy learning method, Differentiable Predictive Control (DPC)…

… An adaptive tracking control algorithm is proposed in [8] for robotic systems with partially …
and input constraints exist. Model predictive control (MPC) is an optimal control strategy that …

… predictive control (MPC) method for robotic manipulators with model uncertainty and input
constraints. In … is introduced as a predictive model for the robotic system with online learning …

… predictive control (GP-based NMPC) algorithm is presented to deal with the visual servoing
problem for constrained mobile robots. … is used to capture the robot dynamics with on-line …

… predictive control to include step distance to the optimization objective function, while made
footsteps variable to generate both CoM and CoP trajectories under the CoP constraints. …

… predictive control (MPC) scheme with friction compensation, subject to incremental control
input constraints and … for a three-wheeled omnidirectional mobile robot (OMR). The proposed …

… control efficiently while regarding several satellite operating restrictions. In this paper, a
parameterized Model Predictive Control (… , the constraints inherent to the model to be controlled, …