[PDF][PDF] Adaptive neural networks based robust output feedback controllers for nonlinear systems

AJ Abougarair, MKI Aburakhis… - … Journal of Robotics …, 2022 - pdfs.semanticscholar.org
The performance of the nonlinear control system that is subjected to uncertainty, can be
enhanced by implementing an adaptive approach by using the robust output-feedback …

[PDF][PDF] Maximum Power Extraction Control Algorithm for Hybrid Renewable Energy System.

N Kanagaraj, M Al-Ansi - Computer Systems Science & Engineering, 2023 - academia.edu
In this research, a modified fractional order proportional integral derivate (FOPID) control
method is proposed for the photovoltaic (PV) and thermoelectric generator (TEG) combined …

Performance of anti-lock braking systems based on adaptive and intelligent control methodologies

AJ Abougarair, NAA Shashoa… - Indonesian Journal of …, 2022 - section.iaesonline.com
Automobiles of today must constantly change their speeds in reaction to changing road and
traffic circumstances as the pace and density of road traffic increases. In sophisticated …

Generalization of Direct Adaptive Control Using Fractional Calculus Applied to Nonlinear Systems

M Aburakhis, R Ordóñez - Journal of Control, Automation and Electrical …, 2024 - Springer
This paper presents a new direct adaptive control (DAC) technique using Caputo's definition
of the fractional-order derivative. This is the first time a fractional-order adaptive law is …

Ball and beam control using adaptive pid based on q-learning

BP Amiruddin, REA Kadir - 2020 7th International Conference …, 2020 - ieeexplore.ieee.org
The ball and beam system is one of the most used systems for benchmarking the controller
response because it has nonlinear and unstable characteristics. Furthermore, in line with the …

[PDF][PDF] Function approximation using a discrete fractional order gradient descent law

M Aburakhis, YN Raffoul - International Journal of Difference …, 2020 - campus.mst.edu
We use discrete fractional calculus (DFC) to generalize the discrete-time gradient descent
law. A discrete fractional-order gradient descent law (DFOGDL) is designed based on …

Adaptive control of nonlinear systems represented by Extreme Learning Machine (ELM) and the Fuzzy Logic Control (FLC)

A Abdusamad, M Aburakhis - 2021 IEEE 1st International …, 2021 - ieeexplore.ieee.org
Extreme learning machine (ELM) has been used in many fields due to its flexibility to
approximate highly nonlinear functions. This is because the hidden node parameters are …

Stand-alone function approximation using fractional order techniques

M Aburakhis, A Abdusamad - 2021 IEEE 1st International …, 2021 - ieeexplore.ieee.org
We have previously showed that there is a possibility to generalize the gradient descent
algorithm to improve the performance of function approximation technique. The Caputo-like …

Artificial neural network approach to improve the performance of battery and thermal storage

S Dauga, I Aldaouab - Smart Structures and NDE for Industry …, 2020 - spiedigitallibrary.org
Energy storage technology and its efficient deployment will be increasingly needed to
manage intermittent of renewable energy supply. Large scale storage can support a power …

New fractional PID-controller to mitigate frequency variations in power systems.

KS Pritam, T Mathur, S Agarwal… - … , Science & Aerospace …, 2020 - search.ebscohost.com
In recent decades, the response of a Fractional Order Proportional Integral Derivative
(FOPID) controller has become subject of interest for many researchers. From literature, it is …