Results 71 to 80 of about 20,183,106 (289)
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
International Journal of Adaptive Control and Signal Processing, EarlyView.This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Benchmarking for nonlinear system identification: Submission platform and baseline results
Data-Centric EngineeringBenchmarking identification methods is essential to validate newly proposed algorithms. The machine learning community has illustrated how benchmarks can be a driver for new developments in the field.
Maarten Schoukens +3 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
On the interpretation and identification of dynamic Takagi-Sugenofuzzy models [PDF]
, 2000 Dynamic Takagi-Sugeno fuzzy models are not always easy to interpret, in particular when they are identified from experimental data. It is shown that there exists a close relationship between dynamic Takagi-Sugeno fuzzy models and dynamic linearization ...
Murray-Smith, R. +5 more
core +1 more source
Nonlinear System Identification of Tremors Dynamics: A Data-driven Approximation Using Koopman Operator Theory. [PDF]
Int IEEE EMBS Conf Neural Eng, 2023 Xue X, Iyer A, Roque D, Sharma N.
europepmc +1 more source
Advanced Engineering Materials, EarlyView.A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source
The design of periodic excitations for dynamic system identification [PDF]
System identification techniques are developed for modelling linear and nonlinear systems. The main results of the work are concerned with the design and utilisation of periodic perturbation signals in general areas of time- and frequency-domain ...
McCormack, Anthony Sean
core
SINDy-SA framework: enhancing nonlinear system identification with sensitivity analysis. [PDF]
Nonlinear Dyn, 2022 Naozuka GT +3 more
europepmc +1 more source
Advanced Engineering Materials, EarlyView.This article presents the design, modeling, and characterization of air‐pressure–actuated programmable vibroacoustic metamaterials (PVAMM). The study focuses on leveraging air pressure to dynamically tune resonance frequencies for effective noise attenuation.
William Kaal +2 more
wiley +1 more source