Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5005469 | ISA Transactions | 2006 | 14 Pages |
Abstract
Increasingly, genetic algorithms (GAs) are used to optimize the parameters of fuzzy logic controllers (FLCs). Although GAs provide a systematic design approach, the optimization process is generally performed off-line using a plant model. Differences between the model and physical plant may result in unsatisfactory control performance when the FLCs are deployed in practice. Type-2 FLCs are an attractive alternative because they can better cope with modeling uncertainties. Unfortunately, type-2 FLCs are computationally intensive. This paper presents a simplified type-2 FLC that is suitable for real-time applications. The key idea is to only replace some critical type-1 fuzzy sets by type-2 sets. Experimental results indicate that the proposed simplified type-2 FLC is as robust as a conventional type-2 FLC, while lowering the computational cost.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Dongrui Wu Woei Wan Tan,