Adaptive neural network based backstepping control design for MIMO nonlinear systems with actuator nonlinearities

Purpose – The purpose of the proposed research methodology is to control the trajectory tracking of EDRM and also to cancel out the effect of no-smooth nonlinearities, which affect the system performance badly. Design/methodology/approach – Robust adaptive neural network (RANN)-based backstepping co...

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Bibliographic Details
Published in:Aircraft Engineering and Aerospace Technology 2016-01, Vol.88 (1), p.137-150
Main Authors: Jamil, Muhammad Usman, Kongprawechnon, Waree, Raza, Muhammad Qamar
Format: Article
Language:English
Subjects:
Adaptive control
Adaptive control systems
Aerospace engineering
Control systems
Controllers
Design engineering
Engineering
Friction
Methodology
MIMO (control systems)
Neural networks
Nonlinear control
Nonlinear systems
Nonlinearity
Robotics
Simulation
Tracking
Tracking control
Trajectories
Trajectory control
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Summary:Purpose – The purpose of the proposed research methodology is to control the trajectory tracking of EDRM and also to cancel out the effect of no-smooth nonlinearities, which affect the system performance badly. Design/methodology/approach – Robust adaptive neural network (RANN)-based backstepping control design methodology is presented in this paper. The proposed design methodology improves the trajectory tracking and running mean error. Findings – The running mean error results show that the convergence of the proposed RANN-based backstepping technique is very fast as compare to the conventional PD control and due to this proposed control technique, the EDRM follows its desired trajectory perfectly. Practical implications – The EDRM trajectory tracking performance increases which leads to a better working position of EDRM. Originality/value – The originality of this research article is 93 per cent.
ISSN:1748-8842
0002-2667
1758-4213
DOI:10.1108/AEAT-09-2014-0150