Stable indirect adaptive control using fuzzy systems and neural networks

摘要: Fuzzy controllers have stirred a great deal of excitement in some circles since they allow for the simple inclusion heuristic knowledge about how to control plant rather than requiring exact mathematical models. This can sometimes lead good controller designs very short period time. In situations where heuristics do not provide enough information specify all parameters fuzzy priori, researchers introduced adaptive schemes that use data gathered during on-line operation controller, and special adaptation heuristics, automatically learn these (see e.g. [1] – [12] or References therein). To date, stability conditions been provided any approaches [12], but Langari Tomizuka [13] others developed (non-adaptive) recently several innovative stable [14] [17]. Moreover, closely related neural studied [18] [23]. this article, we seek introduce an approach which is guaranteed operate properly under less restrictive assumptions more general continuous-time nonlinear systems.