A Suboptimal Approach to Real-time Model Predictive Control of Nonlinear Systems

被引：10

作者：

Graichen, Knut ^{[1
]}

Egretzberger, Markus ^{[2
]}

Kugi, Andreas ^{[2
]}

机构：

[1] Univ Ulm, Inst Mess Regel & Mikrotech, D-89081 Ulm, Germany

[2] TU Wien, Inst Automatisierungs & Regelungstech, A-1040 Vienna, Austria

来源：

AT-AUTOMATISIERUNGSTECHNIK | 2010年 / 58卷 / 08期

关键词：

Model Predictive Control; nonlinear systems; real-time feasibility; time and memory efficient computation; suboptimality; incremental improvement; RECEDING-HORIZON CONTROL; STABILITY; OPTIMALITY; SCHEME;

D O I：

10.1524/auto.2010.0860

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The paper describes a fast Model Predictive Control (MPC) scheme for nonlinear systems subject to control constraints. The MPC scheme computes a suboptimal solution of the underlying optimal control problem that is incrementally refined over the runtime of the process. The MPC scheme uses a fixed number of iterations in each sampling step and allows for a time and memory efficient computation of the single iterations. The control performance, the real-time feasibility as well as the incremental improvement of the MPC scheme are demonstrated for a laboratory overhead crane with a sampling time of 2 ms.

引用

页码：447 / 456

页数：10

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