Abstract—Model Predictive Control (MPC) is a popular optimization-based control technique. MPC is usually formu-lated as sparse or dense Quadratic Programming (QP). This paper …

Model Predictive Control (MPC) is a popular optimization-based control technique. MPC is usually formulated as sparse or dense Quadratic Programming (QP). This paper reviews two well …

Oct 1, 2002 · In this study, we tailor and apply a new QP method, called QPSchur, to large MPC applications, such as cross directional control problems in paper machines. Written in C++, …

Jan 1, 2011 · In this paper, an iterative multiplicative algorithm is proposed for the fast solution of quadratic programming (QP) problems that arise in the real-time implementation of Model …

Sep 29, 2018 · Model predictive control (MPC) is an advanced control strategy that can naturally handle constrained systems with multiple inputs and outputs [57, 69]. However, the …

Model Predictive Control (MPC) has become popular for online robot decision-making. It has shown compelling results with all kinds of robots ranging from industrial manipulators [1], …

Jan 26, 2024 · When applied to model predictive control (MPC) problems for the quadruped robotic platform ANYmal, this method achieves over two orders of magnitude reduction in …

May 2, 2025 · The efficient computation of parametric solution sensitivities is a key challenge in the integration of learning-enhanced methods with nonlinear model predictive control (MPC), …

Jan 1, 2002 · Model Predictive Controllers calculate the optimal control inputs at each time step, based on past information, a plant model, a quadratic objective and given constraints. …

We describe briefly a trust-region feasibility-perturbed sequential quadratic programming algorithm (developed in a companion report), then discuss its adaptation to the problems …