文章基本信息

标题：An Efficient Inexact NMPC Scheme with Stability and Feasibility Guarantees
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作者：Andrea Zanelli ; Andrea Zanelli ; Rien Quirynen 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：18
页码：53-58
DOI：10.1016/j.ifacol.2016.10.139
语种：English
出版社：Elsevier
摘要：Abstract: In this paper, an inexact nonlinear model predictive control scheme with reduced computational complexity is proposed. The presented approach exploits fixed sensitivity information precomputed offline at a reference value. This allows one to avoid the online computational effort resulting from the propagation of sensitivities and possibly the corresponding condensing routine when solving the optimal control problem with a sequential quadratic programming method. By performing a numerical simulation of the nonlinear dynamics online, feasibility of the closed-loop trajectories can be preserved in contrast to linear model predictive control schemes. Nominal stability guarantees of the approach are derived and the effectiveness of the scheme is demonstrated on a non-trivial example.
关键词：Keywordsnonlinear model predictive controlnumerical methodsLyapunov stabilityembedded optimization