eprintid: 3583 rev_number: 6 eprint_status: archive userid: 69 dir: disk0/00/00/35/83 datestamp: 2016-10-10 15:08:08 lastmod: 2016-10-10 15:08:08 status_changed: 2016-10-10 15:08:08 type: article metadata_visibility: show creators_name: Rubagotti, Matteo creators_name: Patrinos, Panagiotis creators_name: Guiggiani, Alberto creators_name: Bemporad, Alberto creators_id: creators_id: creators_id: creators_id: alberto.bemporad@imtlucca.it title: Real-time model predictive control based on dual gradient projection: Theory and fixed-point FPGA implementation ispublished: pub subjects: QA75 divisions: CSA full_text_status: none abstract: This paper proposes a method to design robust model predictive control (MPC) laws for discrete-time linear systems with hard mixed constraints on states and inputs, in case of only an inexact solution of the associated quadratic program is available, because of real-time requirements. By using a recently proposed dual gradient-projection algorithm, it is proved that the discrepancy of the optimal control law as compared with the obtained one is bounded even if the solver is implemented in fixed-point arithmetic. By defining an alternative MPC problem with tightened constraints, a feasible solution is obtained for the original MPC problem, which guarantees recursive feasibility and asymptotic stability of the closed-loop system with respect to a set including the origin, also considering the presence of external disturbances. The proposed MPC law is implemented on a field-programmable gate array in order to show the practical applicability of the method. date: 2016 date_type: published publication: International Journal of Robust and Nonlinear Control volume: 26 number: 15 publisher: Wiley pagerange: 3292-3310 id_number: doi:10.1002/rnc.3507 refereed: TRUE issn: 10498923 official_url: http://doi.org/10.1002/rnc.3507 referencetext: Rawlings JB, Mayne DQ. 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