… combined with ILC for constrained multivariable control. … predictive control (MPC) technique
combined with iterative learning control (ILC), called the iterative learning model predictive …

… 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 …

… 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 …

… 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. …

… Autonomous robotic systems operating in uncertain, realworld environments must be able …
to the system dynamics. Therefore, we propose a constrained, predictive control strategy that …

… robot manipulator by considering robot dynamics without using joint velocity measurements
in the presence of constraints… An approach to design model predictive control (MPC) method …

… Therefore, in this paper, we propose a constrained, predictive control strategy that … ’s
applicability to various classes of robotic system operating in extremely challenging environments or …

… 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 …