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Robust Adaptive Control of an Uninhabited Surface Vehicle
Author(s) -
Andy Annamalai,
Robert Sutton,
Chenguang Yang,
Phil Culverhouse,
Sanjay Sharma
Publication year - 2014
Publication title -
journal of intelligent and robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.631
H-Index - 77
eISSN - 1573-0409
pISSN - 0921-0296
DOI - 10.1007/s10846-014-0057-2
Subject(s) - autopilot , control theory (sociology) , engineering , controller (irrigation) , model predictive control , adaptive control , control engineering , covariance matrix , computer science , control (management) , artificial intelligence , algorithm , agronomy , biology
© 2014, Springer Science+Business Media Dordrecht. A robust adaptive autopilot for uninhabited surface vehicles (USV) based on a model predictive controller (MPC) is presented in this paper. The novel autopilot is capable of handling sudden changes in system dynamics. In real life situations, very often a sudden change in dynamics results in missions being aborted and the uninhabited vehicles have to be rescued before they cause damage to other marine craft in the vicinity. This problem has been suitably dealt with by this innovative design. The MPC adopts an online adaptive nature by utilising three algorithms, individually: gradient descent, least squares and weighted least squares (WLS). Even with random initialisation, significant improvements over the other algorithmic approach were achieved by WLS by maintaining the intermittent continuous values of system parameters and periodically reinitialising the covariance matrix. Also, a time frame of 25 seconds appears to be the optimum to reinitialise the parameters in simulation studies. This novel approach enables the autopilot to cope well with significant changes in the system dynamics and empowers USVs to accomplish their desired missions

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