A review on monitoring and advanced control strategies for precision irrigation
The demand for freshwater is on the increase due to the rapid growth in the world's
population while the effect of global warming and climate change cause severe threat to …
population while the effect of global warming and climate change cause severe threat to …
Neural network-based flight control systems: Present and future
As the first review in this field, this paper presents an in-depth mathematical view of
Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural …
Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural …
[HTML][HTML] Advanced predictive control for GRU and LSTM networks
K Zarzycki, M Ławryńczuk - Information Sciences, 2022 - Elsevier
This article is concerned with Model Predictive Control (MPC) algorithms that use Short
Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural networks for prediction. For …
Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural networks for prediction. For …
LSTM and GRU neural networks as models of dynamical processes used in predictive control: A comparison of models developed for two chemical reactors
K Zarzycki, M Ławryńczuk - Sensors, 2021 - mdpi.com
This work thoroughly compares the efficiency of Long Short-Term Memory Networks
(LSTMs) and Gated Recurrent Unit (GRU) neural networks as models of the dynamical …
(LSTMs) and Gated Recurrent Unit (GRU) neural networks as models of the dynamical …
Neural-network-based nonlinear model predictive control for piezoelectric actuators
Piezoelectric actuators (PEAs) have been widely used in nanotechnology due to their
characteristics of fast response, large mass ratio, and high stiffness. However, hysteresis …
characteristics of fast response, large mass ratio, and high stiffness. However, hysteresis …
[HTML][HTML] Short-term wind speed prediction using Extended Kalman filter and machine learning
S Hur - Energy Reports, 2021 - Elsevier
Wind speed prediction could play an important role in improving the performance of wind
turbine control and condition monitoring. For example, by predicting or forecasting the …
turbine control and condition monitoring. For example, by predicting or forecasting the …
[HTML][HTML] Experimental and developed DC microgrid energy management integrated with battery energy storage based on multiple dynamic matrix model predictive …
This study presents the energy management and control strategy in the islanded DC
microgrid structure in the presence of renewable energy sources (RES) and battery storage …
microgrid structure in the presence of renewable energy sources (RES) and battery storage …
Model predictive control home energy management and optimization strategy with demand response
The growing demand for electricity is a challenge for the electricity sector as it not only
involves the search for new sources of energy, but also the increase of generation capacity …
involves the search for new sources of energy, but also the increase of generation capacity …
Hardware implementation of radial-basis neural networks with Gaussian activation functions on FPGA
This article introduces a method for realizing the Gaussian activation function of radial-basis
(RBF) neural networks with their hardware implementation on field-programmable gaits area …
(RBF) neural networks with their hardware implementation on field-programmable gaits area …
Physics-informed neural nets for control of dynamical systems
Physics-informed neural networks (PINNs) incorporate established physical principles into
the training of deep neural networks, ensuring that they adhere to the underlying physics of …
the training of deep neural networks, ensuring that they adhere to the underlying physics of …