H∞ fuzzy filtering design for non-linear sampled-data systems
| Autor: | Y.-F. Li, C.S. Tseng |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Control and Optimization
Fuzzy set Linear matrix inequality Filter (signal processing) Nonlinear control Hamilton–Jacobi equation Fuzzy logic Computer Science Applications Human-Computer Interaction Nonlinear system Discrete time and continuous time Control and Systems Engineering Control theory Electrical and Electronic Engineering Mathematics |
| Zdroj: | IET Control Theory & Applications. 3:561-574 |
| ISSN: | 1751-8652 1751-8644 |
| DOI: | 10.1049/iet-cta.2007.0418 |
| Popis: | The problem of H∞ filtering design is studied for non-linear sampled-data systems using the Takagi–Sugeno (T–S) fuzzy model approach. The sampled-data filtering is to estimate the states of a continuous-time system using only sampled measurements at discrete instants of time. Traditionally, the sufficient conditions for the existence of such an H∞ filter are characterised in terms of the solution of a differential Hamilton–Jacobi inequality with jumps, which is equivalent to solving the partial differential inequality with jumps. In general, there is no analytical solution for this non-linear partial differential inequality with jumps. First, in this study, the T–S fuzzy model is proposed to represent a class of non-linear sampled-data systems. Next, by using the T–S fuzzy model, the H∞ fuzzy filtering design problem for non-linear sampled-data system is characterised in terms of a linear matrix inequality (LMI) problem. Hence, the H∞ fuzzy filter of non-linear sampled-data systems can be given via solving LMIs instead of solving a differential Hamilton–Jacobi inequality with jumps. To illustrate the results, a numerical example is included. |
| Databáze: | OpenAIRE |
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