Extreme learning-based non-linear model predictive controller for an autonomous underwater vehicle: simulation and experimental results

Extreme learning-based non-linear model predictive controller for an autonomous underwater vehicle: simulation and experimental results

In this study, an extreme learning-based non-linear model predictive controller (NMPC) is proposed for path following planning of an autonomous underwater vehicle (AUV) using horizontal way-points. The proposed controller comprises a kinematic controller and a dynamic controller. The kinematic contr...

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Bibliographic Details
Main Authors: Biranchi Narayan Rath, Bidyadhar Subudhi
Format: Article
Language:English
Published: Wiley 2019-07-01
Series:IET Cyber-systems and Robotics
Subjects:
adaptive control
self-adjusting systems
state feedback
control system synthesis
nonlinear control systems
three-term control
predictive control
h^∞ control
learning systems
autonomous underwater vehicles
optimisation
vehicle dynamics
path planning
control nonlinearities
nmpc approach
auv
elm structure
control algorithms
inverse optimal self-tuning proportional–integral–derivative controller
inverse optimal self-tuning pid controller
autonomous underwater vehicle
kinematic controller design
dynamic controller design
extreme learning-based nonlinear model predictive controller
h(∞) state feedback controller
horizontal way-points
back-stepping approach
extreme learning machine structure
jaya optimisation algorithm
rudder planes
matlab
Online Access:https://digital-library.theiet.org/content/journals/10.1049/iet-csr.2019.0014

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