Multiple Models Book: Fuzzy Control based on linear models
Takagi--Sugeno fuzzy models can provide an effective representation of complex
nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of
linear input--output submodels. Based on such models, two classes of stabilizing
state-feedback controllers: linear time-invariant controllers and fuzzy
controllers, can be designed by means of Linear Matrix Inequality (LMI) methods.
Stability analysis of the fuzzy feedback loop and design of stabilizing
controllers are performed via the use of a quadratic Lyapunov function.
Robustness to uncertainties in the premises or in the consequents of the models,
as well as some performance criteria, can be addressed by solving optimisation
problems using LMIs. This offers a tractable and systematic synthesis technique
to model-based design of fuzzy controllers.
R Murray-Smith
Last modified: Tue Mar 25 16:41:24 GMT