Real‐time model predictive control based on dual gradient projection: Theory and fixed‐point FPGA implementation. (12th January 2016)

• Record Type: Journal Article
• Authors: Rubagotti, Matteo; Patrinos, Panagiotis; Guiggiani, Alberto; Bemporad, Alberto
• Is Part Of: International journal of robust and nonlinear control. Volume 26:Number 15(2016)
• Page Start: 3292
• Page End: 3310
• Publication Date: 2016-01-12
• Subjects: model predictive control -- uncertain systems -- optimization methods; Automatic control -- Periodicals; Control theory -- Periodicals; Nonlinear systems -- Periodicals; 629.836
• DOI: 10.1002/rnc.3507
• Languages: English
• ISSNs: 1049-8923

Abstract

Summary: 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.