Asynchronous H∞ filtering for semi-Markov jump TS fuzzy systems within partial state delay and deception attack: Applied to aircraft-pilot state estimation
B Ren, HR Karimi, T Yin, S Fu - Journal of the Franklin Institute, 2023 - Elsevier
This article addresses an asynchronous filter design problem within partial state delay and
deception attack for a class of discrete-time semi-Markov jump Takagi-Sugeno (TS) systems …
deception attack for a class of discrete-time semi-Markov jump Takagi-Sugeno (TS) systems …
A fuzzy neural controller for model-free control of redundant manipulators with unknown kinematic parameters
In real-world robotics applications, kinematic parameters of redundant manipulators may
need to be changed, thus creating difficulties in achieving precise control. To address this …
need to be changed, thus creating difficulties in achieving precise control. To address this …
A new nonlinear lifting line method for aerodynamic analysis and deep learning modeling of small unmanned aerial vehicles
In this work, a computationally efficient and high-precision nonlinear aerodynamic
configuration analysis method is presented for both design optimization and mathematical …
configuration analysis method is presented for both design optimization and mathematical …
Interval Type-3 TS fuzzy system for nonlinear aerodynamic modeling
This paper presents an aircraft related application of interval type-3 (IT3) TS fuzzy system for
nonlinear aerodynamic modeling from recorded flight data. The theoretical base developed …
nonlinear aerodynamic modeling from recorded flight data. The theoretical base developed …
Flow field reconstructions with gans based on radial basis functions
L Hu, W Wang, Y Xiang, J Zhang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Nonlinear sparse data regression and generation have been a long-term challenge in the
field of aerodynamics, flow field reconstruction is an area of specific interest in this article …
field of aerodynamics, flow field reconstruction is an area of specific interest in this article …
Fuzzy Adaptive Knowledge-Based Inference Neural Networks: Design and Analysis
A novel fuzzy adaptive knowledge-based inference neural network (FAKINN) is proposed in
this study. Conventional fuzzy cluster-based neural networks (FCBNNs) suffer from the …
this study. Conventional fuzzy cluster-based neural networks (FCBNNs) suffer from the …
Periodic self-triggered strategy for highly non-linear hybrid stochastic delayed networks based on impulsive control
This article investigates the stabilization issue of highly non-linear hybrid stochastic delayed
networks (HSDNs) via periodic self-triggered control under impulse (PS-TCI). Firstly, the …
networks (HSDNs) via periodic self-triggered control under impulse (PS-TCI). Firstly, the …
Interval Type-3 Shadowed Sets as an Efficient Way to Approximate Interval Type-3 Fuzzy Systems
Nowadays, one of the most recent realms in Fuzzy Logic is the emergence of Type-3 Fuzzy
Logic, with novel applications and potential to be explored. However, one of the biggest …
Logic, with novel applications and potential to be explored. However, one of the biggest …
Output Linearization of Single-Input Single-Output Fuzzy System to Improve Accuracy and Performance.
QK Peng, MY Noor - Computers, Materials & Continua, 2023 - search.ebscohost.com
For fuzzy systems to be implemented effectively, the fuzzy membership function (MF) is
essential. A fuzzy system (FS) that implements precise input and output MFs is presented to …
essential. A fuzzy system (FS) that implements precise input and output MFs is presented to …
Intermittent Sampled-Data Stabilization of Highly Nonlinear Delayed Stochastic Networks via Periodic Self-Triggered Strategy
This article considers the stabilization issue of highly nonlinear delayed stochastic networks
(HNDSNs) based on periodic self-triggered intermittent control under sampled-data (PICS) …
(HNDSNs) based on periodic self-triggered intermittent control under sampled-data (PICS) …