New optimal fast terminal sliding mode control combined with neural networks for modelling and controlling a drone quadrotor Online publication date: Fri, 27-Oct-2023
by Najlae Jennan; El Mehdi Mellouli
International Journal of Automation and Control (IJAAC), Vol. 17, No. 6, 2023
Abstract: This study concerns the modelling and control of a drone quadrotor which is a multi-input multi-output nonlinear system. The fast terminal sliding mode controller combined with particle swarm optimisation and neural network is presented to control the system, in order to solve high nonlinearity and cross-coupling problems. Generalising the control laws requires the complete state and all the system dynamics. However, not all states are accessible to the control laws and some dynamics cannot be modelled. Therefore, a triangular observer is proposed to estimate the system hidden states based on neural network to approximate the unmodelled dynamic part. We join a supplementary term in the control laws to reduce modelling errors and disturbances. Then, we use particle swarm optimisation to optimise important coefficients to achieve better results. The control laws come from the stability study in sense of Lyapunov. The results simulations confirm the effectiveness of the proposed control strategy.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Automation and Control (IJAAC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook