Real-time model predictive control based on dual gradient projection : Theory and fixed-point FPGA implementation

Copyright © 2016 John Wiley & Sons, Ltd. 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, beca...

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Veröffentlicht in:International Journal of Robust and Nonlinear Control 2016, Vol.26 (15), p.3292-3310
Hauptverfasser: Rubagotti, M, Patrinos, Panos, Guiggiani, A, Bemporad, A
Format: Artikel
Sprache:eng
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Zusammenfassung:Copyright © 2016 John Wiley & Sons, Ltd. 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. Copyright © 2016 John Wiley & Sons, Ltd.
ISSN:1049-8923