Improved radial basis function artificial neural network and exact-time extended state observer based non-singular rapid terminal sliding-mode control of quadrotor …

M Ullah, C Zhao, H Maqsood - Aircraft Engineering and Aerospace …, 2022 - emerald.com
Purpose The purpose of this paper is to design a hybrid robust tracking controller based on
an improved radial basis function artificial neural network (IRBFANN) and a novel extended …

Exponential sliding mode control based on a neural network and finite-time disturbance observer for an autonomous aerial vehicle exposed to environmental …

M Ullah, C Zhao, H Maqsood, M Humayun… - Journal of Control …, 2022 - Springer
The quadrotor system's nonlinear behaviour, uncertain modelling parameters and the
presence of exogenous disturbances in the surrounding environment make its flight control …

Adaptive Neural-Sliding Mode Control of a Quadrotor Vehicle with Uncertainties and Disturbances Compensation

M Ullah, C Zhao, H Maqsood, A Nasir… - 2022 2nd …, 2022 - ieeexplore.ieee.org
This paper addresses the quadrotor vehicle control problem in the presence of parametric
uncertainties and exogenous disturbances by introducing a finite-time extended disturbance …

Adaptive-Neural Finite-Time Sliding Mode Control for Quadrotor Helicopter Attitude Stabilization in Complex Environments

M Ullah, G Hongbo, W Chengbo… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Achieving attitude stabilization in quadrotor helicopters (qh s) operating in complex
environments, characterized by external disturbances and model uncertainties, presents a …

Adaptive Sliding Mode Control with an Extended Disturbance Observer for a Quadcopter Unmanned Aerial Vehicle: A Finite-Time Convergent Approach

SU Khan, H Gao, X Xu, C Feng… - 2023 7th CAA …, 2023 - ieeexplore.ieee.org
Robust flight control always plays an important role in the accurate tracking of the desired
path by the quadcopter vehicle. The hybrid strategy used for this purpose proved quite …

Chaos Detection and Mitigation in Swarm of Drones Using Machine Learning Techniques and Chaotic Attractors

N Emmanuel, LS Mistura… - International …, 2022 - search.proquest.com
Most existing identification and tackling of chaos in swarm drone missions focus on single
drone scenarios. There is a need to assess the status of a system with multiple drones …

[PDF][PDF] Chaos Detection and Mitigation in Swarm of Drones using Machine Learning Techniques and Chaotic Attractors

E NEBE, ML SANNI, RA ADETONA, BO AKINYEMI… - Chaos, 2022 - academia.edu
Most existing identification and tackling of chaos in swarm drone missions focus on single
drone scenarios. There is a need to assess the status of a system with multiple drones …