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Maryam Shahriari-kahkeshi

Researcher at Shahrekord University

Publications -  26
Citations -  239

Maryam Shahriari-kahkeshi is an academic researcher from Shahrekord University. The author has contributed to research in topics: Nonlinear system & Fuzzy logic. The author has an hindex of 6, co-authored 24 publications receiving 153 citations. Previous affiliations of Maryam Shahriari-kahkeshi include Isfahan University of Technology.

Papers
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Entropy Analysis and Neural Network-Based Adaptive Control of a Non-Equilibrium Four-Dimensional Chaotic System with Hidden Attractors

TL;DR: This paper presents a non-equilibrium four-dimensional chaotic system with hidden attractors and investigates its dynamical behavior using a bifurcation diagram, as well as three well-known entropy measures, such as approximate entropy, sample entropy, and Fuzzy entropy.
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Adaptive fault detection and estimation scheme for a class of uncertain nonlinear systems

TL;DR: In this article, a fault detection and estimation (FDE) scheme for a class of Lipschitz nonlinear systems subjected to modeling and measurement uncertainties is presented, which is based on an adaptive diagnostic observer that not only estimates the states of the system and generates the residual signal simultaneously, but also is able to estimate the characteristic and magnitude of an unknown fault.
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Adaptive fuzzy wavelet network for robust fault detection and diagnosis in non-linear systems

TL;DR: In this paper, an adaptive fuzzy wavelet network-based fault detection and diagnosis (AFWN-FDD) scheme is proposed for non-linear systems subject to unstructured uncertainty.
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An Adaptive Estimator-Based Sliding Mode Control Scheme for Uncertain POESLL Converter

TL;DR: An adaptive estimator-based sliding mode control scheme for the POSELL converter considering a reduced-order model of the converter with an unknown load and unknown input voltage and the ability of the proposed scheme for voltage regulation as well as its robustness against parameter uncertainties is verified.
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Distributed adaptive consensus tracking control for uncertain non-linear multi-agent systems with input saturation

TL;DR: This study proposes a novel distributed adaptive consensus control scheme for a class of uncertain non-linear multi-agent systems with unknown control gains and input saturation that solves the `singularity' problem without using the projection operator.