Name
Abstract | ||
|---|---|---|
In this paper the design of unknown inputs proportional integral observers for Takagi-Sugeno (TS) fuzzy models subject to unmeasurable decision variables is proposed. These unknown inputs affect both state and output of the system. The synthesis of these observers is based on two hypotheses that the unknown inputs are under the polynomials form with their kth derivatives zero for the first one and bounded norm for the second one, hence two approaches. The Lyapunov theory and L"2-gain technique are used to develop the stability conditions of such observers in LMIs (linear matrix inequality) formulation. A simulation example is given to validate and compare the proposed design conditions for these two approaches. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.neucom.2013.06.024 | Neurocomputing |
Keywords | Field | DocType |
fuzzy model,2-gain technique,proportional integral observer,unknown input,lyapunov theory,linear matrix inequality,kth derivative,decision variable,proposed design condition,polynomials form,ts fuzzy model,bounded norm | Lyapunov function,Decision variables,Polynomial,Control theory,Fuzzy logic,Stability conditions,Mathematics,Linear matrix inequality,Bounded function | Journal |
Volume | ISSN | Citations |
123, | 0925-2312 | 13 |
PageRank | References | Authors |
0.70 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| T. Youssef | 1 | 68 | 2.39 |
| M. Chadli | 2 | 39 | 3.35 |
| H. R. Karimi | 3 | 3569 | 223.59 |
| M. Zelmat | 4 | 25 | 2.68 |