State-feedback MPC with piecewise constant control for continuous-time nonlinear systems

被引：0

作者：

Magni, L ^{[1
]}

Scattolini, R ^{[1
]}

机构：

[1] Dipartimento Informat & Sistemist, I-27100 Pavia, Italy

来源：

PROCEEDINGS OF THE 41ST IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-4 | 2002年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new Model Predictive Control (MPC) algorithm for nonlinear systems is presented. The plant under control, the state and control constraints and the performance index to be minimized are described in continuous time, while the manipulated variables are allowed to change at fixed and uniformly distributed sampling times. In so doing, the optimization is performed with respect to sequences, as in discrete time nonlinear MPC, but the continuous time evolution of the system is considered and the approximate plant discretization is avoided, as in continuous time nonlinear AIPC.

引用

页码：4625 / 4630

页数：6

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