Real-Time Sequential Convex Programming for Optimal Control Applications

Tran Dinh Quoc (), Carlo Savorgnan () and Moritz Diehl ()
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Tran Dinh Quoc: K.U. Leuven, Department of Electrical Engineering (ESAT-SCD) and Optimization in Engineering Center (OPTEC)
Carlo Savorgnan: K.U. Leuven, Department of Electrical Engineering (ESAT-SCD) and Optimization in Engineering Center (OPTEC)
Moritz Diehl: K.U. Leuven, Department of Electrical Engineering (ESAT-SCD) and Optimization in Engineering Center (OPTEC)

A chapter in Modeling, Simulation and Optimization of Complex Processes, 2012, pp 91-102 from Springer

Abstract: Abstract This paper proposes real-time sequential convex programming (RTSCP), a method for solving a sequence of nonlinear optimization problems depending on an online parameter. We provide a contraction estimate for the proposed method and, as a byproduct, a new proof of the local convergence of sequential convex programming. The approach is illustrated by an example where RTSCP is applied to nonlinear model predictive control.

Keywords: Model Predictive Control; Sequential Quadratic Programming; Interior Point Method; Nonlinear Model Predictive Control; Model Predictive Control Algorithm (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-25707-0_8

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DOI: 10.1007/978-3-642-25707-0_8

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