Learning Model Predictive Control for Periodic Repetitive Tasks

• Main Authors: Scianca, Nicola, Rosolia, Ugo, Borrelli, Francesco
• Format: Journal Article
• Language: English
• Published: 18-11-2019
• Subjects: Computer Science - Systems and Control
• DOI: 10.48550/arxiv.1911.07535

We propose a reference-free learning model predictive controller for periodic
repetitive tasks. We consider a problem in which dynamics, constraints and
stage cost are periodically time-varying. The controller uses the closed-loop
data to construct a time-varying terminal set and a time-varying terminal cost.
We show that the proposed strategy in closed-loop with linear and nonlinear
systems guarantees recursive constraints satisfaction, non-increasing open-loop
cost, and that the open-loop and closed-loop cost are the same at convergence.
Simulations are presented for different repetitive tasks, both for linear and
nonlinear systems.