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Indirect adaptive control of a class of marine vehicles
Author(s) -
Morel Yannick,
Leonessa Alexander
Publication year - 2010
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.1128
Subject(s) - control theory (sociology) , tracking error , parametric statistics , adaptive control , nonlinear system , bounded function , convergence (economics) , lyapunov function , exponential stability , stability (learning theory) , lyapunov stability , tracking (education) , computer science , set (abstract data type) , mathematics , control (management) , artificial intelligence , psychology , mathematical analysis , pedagogy , statistics , physics , quantum mechanics , machine learning , economics , programming language , economic growth
A nonlinear adaptive framework for bounded‐error tracking control of a class of non‐minimum phase marine vehicles is presented. The control algorithm relies on a special set of tracking errors to achieve satisfactory tracking performance while guaranteeing stable internal dynamics. First, the design of a model‐based nonlinear control law, guaranteeing asymptotic stability of the error dynamics, is presented. This control algorithm solves the tracking problem for the considered class of marine vehicles, assuming full knowledge of the system model. Then, the analysis of the zero‐dynamics is carried out, which illustrates the efficacy of the chosen set of tracking errors in stabilizing the internal dynamics. Finally, an indirect adaptive technique, relying on a partial state predictor, is used to address parametric uncertainties in the model. The resulting adaptive control algorithm guarantees Lyapunov stability of the errors and parameter estimates, as well as asymptotic convergence of the errors to zero. Numerical simulations illustrate the performance of the adaptive algorithm. Copyright © 2009 John Wiley & Sons, Ltd.