Monitoring Control Updating Period In Fast Gradient Based NMPC
This work addresses real-time control challenges for fast dynamic systems, but it appears incremental as it builds on existing fast-gradient MPC schemes with a specific monitoring enhancement.
The paper tackles the problem of determining the optimal control updating period in fast-gradient-based Model Predictive Control (MPC) for systems with fast dynamics, proposing an online monitoring method that uses cheap computations based on algorithm behavior to recover this period in terms of cost function decrease, with efficiency assessed using a constrained triple integrator example.
In this paper, a method is proposed for on-line monitoring of the control updating period in fast-gradient-based Model Predictive Control (MPC) schemes. Such schemes are currently under intense investigation as a way to accommodate for real-time requirements when dealing with systems showing fast dynamics. The method needs cheap computations that use the algorithm on-line behavior in order to recover the optimal updating period in terms of cost function decrease. A simple example of constrained triple integrator is used to illustrate the proposed method and to assess its efficiency.