This paper proposes a transformation method capable of transforming analytically given differential equations of dynamic models into Takagi-Sugeno fuzzy inference model (TS fuzzy model), whereupon various parallel distributed compensation (PDC) controller design techniques can readily be executed. Joining the transformation method and the PDC techniques leads to a controller design framework. The transformation method is specialized to minimize the number of fuzzy rules in the resulting TS fuzzy model according to a given acceptable transformation error, the PDC design thus results in a computational complexity minimized controller which is highly desired in many cases of real applications. The paper presents examples to show the effectiveness of the proposed transformation.
- Complexity reduction
- Higher order singular value decomposition
- Parallel distributed compensation controller design
- Takagi-Sugeno fuzzy inference model
ASJC Scopus subject areas
- Computer Science(all)