Multi-model predictive control based on the Takagi-Sugeno fuzzy models: a case study
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Multiple fuzzy model-based temperature predictive control for HVAC systems
Information Sciences: an International Journal
Robust stability and stabilization for uncertain Takagi--Sugeno fuzzy time-delay systems
Fuzzy Sets and Systems
Control of systems integrating logic, dynamics, and constraints
Automatica (Journal of IFAC)
Stabilizing low complexity feedback control of constrained piecewise affine systems
Automatica (Journal of IFAC)
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Fuzzy modeling of dynamical systems can be viewed as an interpolation of a collection of linear models where the interpolation coefficients depend on set membership functions. The fuzzy interference applies only when the membership functions intersect otherwise only one model is valid. The approach presented in this paper models the intersections with an uncertainty measure reducing the overall fuzzy model to Piecewise Affine (PWA) description, over-approximating the original fuzzy model. Once such an approximation is calculated, existing algorithms can be applied which yield controllers guaranteeing closed-loop stability. Since the PWA model over-approximates a given fuzzy model, if such a controller is calculated, it guarantees stability of the original fuzzy model as well.