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Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3347-y
Abstract: With directly considering the unknown and bounded disturbance, a RBF-ARX model-based two-stage scheduling quasi-min–max robust predictive control (RBF-ARX-TRPC) algorithm for output-tracking control is proposed for a class of smooth nonlinear systems with unknown steady-state knowledge.…
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Keywords:
state;
bounded disturbance;
rbf arx;
arx model ... See more keywords
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2
Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3263180
Abstract: For many practical industrial objects with time-varying operating points, strong nonlinearity, and difficulty in obtaining analytical models, the data-driven identification method is usually used to model such nonlinear systems. However, it is difficult for traditional…
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Keywords:
arx;
control;
deep learning;
model ... See more keywords
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Published in 2020 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2018.2810277
Abstract: A stochastic gradient (SG)-based particle filter (SG-PF) algorithm is developed for an ARX model with nonlinear communication output in this paper. This ARX model consists of two submodels, one is a linear ARX model and…
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Keywords:
particle filter;
communication;
model;
output ... See more keywords
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Published in 2023 at "Biomimetics"
DOI: 10.3390/biomimetics8020141
Abstract: In this article, a chaotic computing paradigm is investigated for the parameter estimation of the autoregressive exogenous (ARX) model by exploiting the optimization knacks of an improved chaotic grey wolf optimizer (ICGWO). The identification problem…
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Keywords:
chaotic grey;
identification;
model;
arx model ... See more keywords