Real-time implementation of optimisation-based control and trajectory planning can be very
challenging for nonlinear systems. As a result, if an implementation based on a fixed …

Today's world is changing rapidly due to advancements in information technology,
computation and communication. Actuation, communication, sensing, and control are …

In this paper, NMPC schemes based on fast update methods (fast NMPC schemes) are
reviewed that strive to provide a fast but typically suboptimal update of the control variables …

This overview paper reviews numerical methods for solution of optimal control problems in
real-time, as they arise in nonlinear model predictive control (NMPC) as well as in moving …

Integration of real-time optimization and control with higher level decision-making
(scheduling and planning) is an essential goal for profitable operation in a highly …

Widespread application of dynamic optimization with fast optimization solvers leads to
increased consideration of first-principles models for nonlinear model predictive control …

We present a reinforcement learning-based (RL) model predictive control (MPC) method for
trajectory tracking of surface vessels. The proposed method uses an MPC controller in order …

A Newton-type method is investigated for online optimisation in nonlinear model predictive
control, the so-called real-time iteration scheme. Only one Newton-type iteration is …

This brief presents a nonlinear model predictive control (NMPC) method for the trajectory
tracking problem of an autonomous underwater vehicle (AUV). By augmenting the desired …

Traditionally, economic optimization and control of chemical processes have been
addressed with a hierarchical approach. In the upper layer, a static economic optimization …