2019/11/18 by Nicola Scianca, Scianca, Nicola, Ugo Rosolia +3
Computer Science · Engineering · #FOS: Electrical engineering #Systems and Control (eess.SY) #cs.SY #eess.SY #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1911.07535
2020 European Control Conference, Saint Petersburg, Russia. Extended version of the conference paper
arxiv created 2020/04/17 · arxiv updated 2020/04/20
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.