Name
Abstract | ||
|---|---|---|
One of the typical important criteria to be considered in real-time control applications is the computational complexity of the controllers, observers, and models applied. In this paper, a singular value decomposition (SVD)-based complexity reduction technique is proposed for Takagi Sugeno (TS) fuzzy models. The main motivation is that the TS fuzzy model has exponentially growing computational complexity with the improvement of its approximation property through, as usually practiced, increasing the density of antecedent terms. The reduction technique proposed here is capable of defining the contribution of each local linear model included in the TS fuzzy model, which serves to remove the weakly contributing ones as according to a given threshold. Reducing the number of models leads directly to the computational complexity reduction. This work also includes a number of numerical and application examples |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/41.993277 | Industrial Electronics, IEEE Transactions |
Keywords | Field | DocType |
computational complexity,control system analysis,fuzzy set theory,singular value decomposition,SVD-based complexity reduction,TS fuzzy models,Takagi Sugeno fuzzy models,controllers,fuzzy rule base reduction,local linear model,observers,real-time control,singular value decomposition | Neuro-fuzzy,Mathematical optimization,Fuzzy classification,Defuzzification,Control theory,Fuzzy set operations,Fuzzy measure theory,Fuzzy logic,Reduction (complexity),Fuzzy number,Mathematics | Journal |
Volume | Issue | ISSN |
49 | 2 | 0278-0046 |
Citations | PageRank | References |
13 | 1.23 | 13 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Baranyi, P. | 1 | 342 | 21.73 |
| Yeung Yam | 2 | 494 | 55.37 |
| Annamária R. Várkonyi-Kóczy | 3 | 27 | 5.08 |
| R. J. Patton | 4 | 44 | 4.77 |
| P. Michelberger | 5 | 13 | 1.23 |
| M. Sugiyama | 6 | 13 | 1.23 |