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Št. zadetkov: 3
Evolving granular fuzzy control
Daniel Leite, Reinaldo Palhares, Igor Škrjanc, Fernando Gomide
Izvirni znanstveni članek
Oznake: samorazvijajoči se sistemi;sprotno aktivno učenje iz toka podatkov;avtonomni razvoj skupine modelov;evolving fuzzy systems;on-line active learning from streams;autonomous evolution of ensemble members;
This paper highlights the relevance of evolving granular fuzzy systems in adaptive control and fuzzy modeling, particularly for learning in dynamic, nonstationary environments. These systems incrementally construct rule-based models—such as predictors and controllers operating in open- or closed-loo ...
Leto: 2026 Vir: Fakulteta za elektrotehniko (UL FE)
Inverse fuzzy model control
Igor Škrjanc, Daniel Leite, Fernando Gomide, Simon Tomažič
Izvirni znanstveni članek
Oznake: vodenje na podlagi podatkov;regulacija temperature;sistemi Takagi–Sugeno;identfikacija nelinearnih sistemov;inverzno mehko vodenje;vodenje toplotnih procesov;data-driven control;temperature control;Takagi– Sugeno systems;nonlinear system identification;inverse fuzzy control;thermal process control;
Inverse fuzzy model control (IFMC) is an attractive strategy for regulating nonlinear thermal processes, where complex heat-transfer dynamics, disturbances, and actuator constraints challenge conventional control approaches. However, traditional direct and indirect inverse schemes often exhibit limi ...
Leto: 2026 Vir: Fakulteta za elektrotehniko (UL FE)
Advancements in data-driven evolving fuzzy and neuro-fuzzy control
Goran Andonovski, Daniel Leite, Radu-Emil Precup, Fernando Gomide, Mahardhika Pratama, Igor Škrjanc
Pregledni znanstveni članek
Oznake: inkrementalno strojno učenje;mehki sistemi;nevronske mreže;adaptivno in sprotno vodenje;vodenje na osnovi podatkov;incremental machine learning;fuzzy systems;neural networks;adaptive and real-time control;data-driven control;
In an era of increasing system complexity and growing demands for autonomy and efficiency, control systems must continuously adapt to dynamic and uncertain environments. This study presents a comprehensive survey of evolving fuzzy and neuro-fuzzy controllers, with emphasis on data-driven control sys ...
Leto: 2026 Vir: Fakulteta za elektrotehniko (UL FE)
Št. zadetkov: 3
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