Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.23919/ECC51009.2020.9143857 | 2020 European Control Conference (ECC) |
DocType | ISBN | Citations |
Conference | 978-3-90714-402-2 | 1 |
PageRank | References | Authors |
0.36 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicola Scianca | 1 | 12 | 4.75 |
| Ugo Rosolia | 2 | 41 | 7.84 |
| Francesco Borrelli | 3 | 1466 | 147.53 |