Robust Model Predictive Control with Almost Zero Online Computation

Yan Yan and Longge Zhang
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Yan Yan: Department of Mathematics and Physics, North China Electric Power University, Baoding 071003, China
Longge Zhang: Department of Mathematics and Physics, North China Electric Power University, Baoding 071003, China

Mathematics, 2021, vol. 9, issue 3, 1-10

Abstract: 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.

Keywords: robust model predictive control; shrinking; linear matrix inequality; robust control (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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