Applied system identification
A case study of grey box identification
Automatica (Journal of IFAC)
Identification of non-linear system structure and parameters using regime decomposition
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Modern control systems engineering
Modern control systems engineering
Evolving rule-based models: a tool for design of flexible adaptive systems
Evolving rule-based models: a tool for design of flexible adaptive systems
Combining GP operators with SA search to evolve fuzzy rule based classifiers
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
How to be a gray box: dynamic semi-physical modeling
Neural Networks
Cluster Analysis for Data Mining and System Identification
Cluster Analysis for Data Mining and System Identification
Sampling Method for Robust Fuzzy Optimization
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
Higher order models for fuzzy random variables
Fuzzy Sets and Systems
Obtaining transparent models of chaotic systems with multi-objective simulated annealing algorithms
Information Sciences: an International Journal
Numerical Recipes 3rd Edition: The Art of Scientific Computing
Numerical Recipes 3rd Edition: The Art of Scientific Computing
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Genetic Fuzzy Systems: Recent Developments and Future Directions; Guest editors: Jorge Casillas, Brian Carse
Genetic learning of fuzzy rules based on low quality data
Fuzzy Sets and Systems
Original article: Dynamic energy model of a lithium-ion battery
Mathematics and Computers in Simulation
Upper and lower probabilities induced by a fuzzy random variable
Fuzzy Sets and Systems
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Intelligent Systems, Design and Applications (ISDA 2009)
Interval-valued GA-P algorithms
IEEE Transactions on Evolutionary Computation
An approach to online identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
FLEXFIS: A Robust Incremental Learning Approach for Evolving Takagi–Sugeno Fuzzy Models
IEEE Transactions on Fuzzy Systems
Brief Open-loop worst-case identification of nonSchur plants
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Hi-index | 0.00 |
A methodology for designing semi-physical fuzzy models is proposed. Prior physical knowledge about the dynamics of the system is modeled with continuous time differential equations. Fuzzy knowledge bases are embedded in these equations as nonlinear constructive blocks. Rules comprising the knowledge bases are fitted to interval-valued data with metaheuristics. A possibilistic filter is proposed that is able to gradually evolve an initial estimation of the latent variables of the model on the basis of successive prediction errors. This methodology has been applied to the prediction of voltage and state of charge of LiFePO"4 batteries. An empirical study has been carried over data gathered in experiments at the Battery Laboratory at Oviedo University. Fitting between the proposed model and actual measurements is studied for four different manufacturers and different charge-discharge patterns. Predictions of the evolution of the voltage during charge, discharge and inactivity compare favorably to different models in the literature. The possibilistic filter allows to estimate the state of charge of batteries after an arbitrary path that may include partial charges and discharges. It is shown that the accuracy of the open loop model improves that of other approaches in the literature, and at the same time the observer-based online model is able to approximate the effective remnant charge of the battery after a reasonably short time.