Autonomous learning for fuzzy systems: a review
As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …
Multi-objective high-dimensional multi-fractional-order optimization algorithm for multi-objective high-dimensional multi-fractional-order optimization controller …
L Yin, W Ding - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Aiming at the operation control of doubly-fed induction generator-wind energy systems, this
study firstly introduces multi-dimensional information feedback and fractional-order theory …
study firstly introduces multi-dimensional information feedback and fractional-order theory …
Real time adaptive probabilistic recurrent Takagi-Sugeno-Kang fuzzy neural network proportional-integral-derivative controller for nonlinear systems
This paper presents an adaptive probabilistic recurrent Takagi-Sugeno-Kang fuzzy neural
PID controller for handling the problems of uncertainties in nonlinear systems. The proposed …
PID controller for handling the problems of uncertainties in nonlinear systems. The proposed …
Self-evolving fuzzy controller composed of univariate fuzzy control rules
The paper proposes a methodology to online self-evolve direct fuzzy logic controllers
(FLCs), to deal with unknown and time-varying dynamics. The proposed methodology self …
(FLCs), to deal with unknown and time-varying dynamics. The proposed methodology self …
Investigation of the optimal pid-like fuzzy logic controller for ball and beam system with improved quantum particle swarm optimization
OT Altinoz, AE Yilmaz - International Journal of Computational …, 2022 - World Scientific
Fuzzy Logic Controllers (FLCs) are intelligent control methods, where membership functions
and corresponding rules are defined to get a proper control signal. The parameters were …
and corresponding rules are defined to get a proper control signal. The parameters were …
Observer-Based Fuzzy PID Control for Nonlinear Systems With Degraded Measurements: Dealing With Randomly Perturbed Sampling Periods
Y Wang, Z Wang, L Zou, Q Ge… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This article addresses the problem of observer-based fuzzy proportional-integral-derivative
(PID) control for a class of nonlinear systems subject to degraded measurements and …
(PID) control for a class of nonlinear systems subject to degraded measurements and …
Self-evolving fuzzy system based inverse dynamics learning control for nonlinear systems with uncertainties
J Pan, T Zhao - Nonlinear Dynamics, 2025 - Springer
This paper develops a self-evolving fuzzy-based inverse dynamics controller with adaptive
thresholds (SEFIDLC) for improving the control performance of uncertain nonlinear systems …
thresholds (SEFIDLC) for improving the control performance of uncertain nonlinear systems …
Adaptive nonparametric evolving fuzzy controller for uncertain nonlinear systems with dead zone
This paper presents an adaptive nonparametric evolving fuzzy controller for uncertain
nonlinear systems with dead zone. The unknown nonlinear-ities caused by the dead zone …
nonlinear systems with dead zone. The unknown nonlinear-ities caused by the dead zone …
Multivariable Evolving Fuzzy Modeling Approach with Time Varying Order State Space
ABF Júnior, GL de Oliveira Serra - Anais do XIX Encontro Nacional …, 2022 - sol.sbc.org.br
Neste trabalho, é apresentada uma metodologia para a identificação de sistemas dinâmicos
multivariável não lineares via modelo nebuloso evolutivo. O modelo evolutivo obtido é …
multivariável não lineares via modelo nebuloso evolutivo. O modelo evolutivo obtido é …