Open AccessControl and synchronization in chaotic systems based on fast linear predictive control
Author(s) -
Yuan Zhang,
Qi Xu,
Sun Mingwei,
Chen Zengqiang
Publication year - 2015
Publication title -
acta physica sinica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.64.010502
Subject(s) - control theory (sociology) , integrator , computer science , chaotic , nonlinear system , observer (physics) , model predictive control , diophantine equation , synchronization (alternating current) , state observer , linear system , matrix (chemical analysis) , control (management) , mathematics , bandwidth (computing) , artificial intelligence , physics , channel (broadcasting) , computer network , mathematical analysis , materials science , discrete mathematics , quantum mechanics , composite material
A kind of fast linear generalized predictive control (GPC) algorithm is proposed based on the extended state observer for chaotic (hyperchaotic) systems. The linear extended state observer is employed to estimate and compensate the nonlinear dynamics and the existing uncertainties of the chaotic (hyperchaotic) systems so that an integrator can be obtained to serve as the model for GPC design. Using this scheme, the computational complexity can be substantially reduced. A step coefficient matrix can be derived analytically and a future output prediction can be explicitly calculated by only using the last two samples of the output. Therefore, the self-tuning algorithms and the Diophantine equation can be completely avoided. The proposed method can be used to control nonlinear targets in a straightforward manner. Simulation results show the effectiveness of this linear algorithm.
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