4.7 Article

Robust Model Predictive Control with Almost Zero Online Computation

期刊

MATHEMATICS
卷 9, 期 3, 页码 -

出版社

MDPI
DOI: 10.3390/math9030242

关键词

robust model predictive control; shrinking; linear matrix inequality; robust control

资金

  1. National Nature Science Foundation of China Scholarship Council [201706735054]
  2. Hebei Provincial Natural Science Foundation [F2016502025]

向作者/读者索取更多资源

This paper presents a strategy for robust model predictive control of constrained, discrete-time systems with state and output disturbances using the linear matrix inequality method. The biggest advantage of this method is the nearly zero online computation, making it applicable to systems with slowly varying and fast changing parameters. A simulation example demonstrates the effectiveness of the proposed technique.
This paper provides a strategy for the problem of robust model predictive control of constrained, discrete-time systems with state and output disturbances. Using the linear matrix inequality (LMI) method, the nested geometric proportion asymptotically stable ellipsoid (GPASE) strategy is designed off-line, and then the designed shrinking ellipsoids strategy assures the system converges on the equivalent with an exponential convergence velocity. The biggest advantage of this method is the online computation is almost reduced to zero, which makes it possible to apply the designed control scheme not only to plants with slowly varying parameters, but also to fast ones. Finally, a simulation example shows the validity of the proposed technique.

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