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Robust Model Predictive Control through Adjustable Variables: an application to Path Planning
 

Summary: Robust Model Predictive Control through Adjustable Variables:
an application to Path Planning
Alessandro Abate* and Laurent El Ghaoui*
Abstract-- Robustness in Model Predictive Control (MPC) is
the main focus of this work. After a definition of the conceptual
framework and of the problem's setting, we will analyze
how a technique developed for studying robustness in Convex
Optimization can be applied to address the problem of robust-
ness in the MPC case. Therefore, exploiting this relationship
between Control and Optimization, we will tackle robustness
issues for the first setting through methods developed in the
second framework. Proofs for our results are included. As an
application of this Robust MPC result, we shall consider a Path
Planning problem and discuss some simulations thereabout.
I. INTRODUCTION
Model Predictive Control is a methodology intended to
devise, given an explicit model of a system, sequences
of control inputs which could be dynamically updated as
soon as new observations of the output may be available
throughout time. These controls are obtained as the result

  

Source: Abate, Alessandro - Faculty of Mechanical, Maritime and Materials Engineering, Technische Universiteit Delft

 

Collections: Engineering