Parameter estimation for a controlled autoregressive autoregressive moving average system based on a recursive framework

L Li, J Zhang, H Zhang, X Ren - Applied Mathematical Modelling, 2023 - Elsevier
In this paper, an adaptive recursive estimation scheme based on a novel recursive
framework is proposed for a controlled autoregressive autoregressive moving average …

Towards lifelong learning of recurrent neural networks for control design

F Bonassi, J Xie, M Farina… - 2022 European control …, 2022 - ieeexplore.ieee.org
This paper proposes a method for lifelong learning of Recurrent Neural Networks, such as
NNARX, ESN, LSTM, and GRU, to be used as plant models in control system synthesis. The …

Hyperparameter optimization for the LSTM method of AUV model identification based on Q-learning

D Wang, J Wan, Y Shen, P Qin, B He - Journal of Marine Science and …, 2022 - mdpi.com
An accurate mathematical model is a basis for controlling and estimating the state of an
Autonomous underwater vehicle (AUV) system, so how to improve its accuracy is a …

Unmanned and autonomous systems: Future of automation in process and energy industries

F Borghesan, M Zagorowska, M Mercangöz - IFAC-PapersOnLine, 2022 - Elsevier
Process and energy industries have been recognised as adopters of high levels of
automation compared to other sectors. Nonetheless, human cognitive input still plays a …

Interactive attention-based capsule network for click-through rate prediction

S Xue, C He, Z Hua, S Li, G Wang, L Cao - IEEE Access, 2024 - ieeexplore.ieee.org
With the continuous penetration of Internet applications in our lives, the ever-increasing data
on clicking behavior has made online services a critical component of the economic sectors …