Journal
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
Volume 28, Issue 10, Pages 3403-3421Publisher
WILEY
DOI: 10.1002/rnc.4088
Keywords
gain scheduling; linear parameter-varying; local performance; particle swarm optimization; switched system
Funding
- Natural Sciences and Engineering Research Council of Canada
- Vanier Canada Graduate Scholarship
- Canada Research Chairs
- Institute for Computing, Information and Cognitive Systems
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This paper presents a novel approach to designing switching linear parameter-varying (SLPV) controllers with improved local performance and an algorithm for optimizing switching surfaces to further improve the performance of the SLPV controllers. The design approach utilizes the weighted average of the local L-2-gain bounds (representing the local performance) as the cost function to be minimized, whereas the maximum of the local L-2-gain bounds (representing the worst-case performance over all subsets) is bounded with a tuning parameter. The tuning parameter is useful for taking the trade-off between the local performance and the worst-case performance. An algorithm based on the particle swarm optimization is introduced to optimize the switching surfaces of an SLPV controller. The efficacy of the proposed SLPV controller design approach and switching surface optimization algorithm is demonstrated on both a numerical example and a physical example of air-fuel ratio control of an automotive engine.
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