Results 91 to 100 of about 24,564,249 (381)

Estimation of Power System Inertia Using Nonlinear Koopman Modes

, 2018
We report a new approach to estimating power system inertia directly from time-series data on power system dynamics. The approach is based on the so-called Koopman Mode Decomposition (KMD) of such dynamic data, which is a nonlinear generalization of ...
Hamasaki, Ryo, Ishigame, Atsushi, Susuki, Yoshihiko   +2 more
core   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

International Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez, Mauro Gaggero, Andrea Serani   +2 more
wiley   +1 more source

Resonantly enhanced second- and third-harmonic generation in dielectric nonlinear metasurfaces

Opto-Electronic Advances
Nonlinear dielectric metasurfaces provide a promising approach to control and manipulate frequency conversion optical processes at the nanoscale, thus facilitating both advances in fundamental research and the development of new practical applications in
Ji Tong Wang, Pavel Tonkaev, Kirill Koshelev, Fangxing Lai, Sergey Kruk, Qinghai Song, Yuri Kivshar, Nicolae C. Panoiu   +7 more
doaj   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Nonlinear energy transfer in classical and quantum systems

, 2012
We investigate the effect of slowly-varying parameter on the energy transfer in a system of weakly coupled nonlinear oscillators, with special attention to a mathematical analogy between the classical energy transfer and quantum transitions.
Kovaleva, Agnessa, Manevitch, Leonid
core   +1 more source

Performance Triggered Adaptive Model Reduction for Soil Moisture Estimation in Precision Irrigation

International Journal of Adaptive Control and Signal Processing, EarlyView.
ABSTRACT Accurate soil moisture information is essential for precise irrigation to enhance water use efficiency. Estimating soil moisture based on limited soil moisture sensors is especially critical for obtaining comprehensive soil moisture information when dealing with large‐scale agricultural fields.
Sarupa Debnath, Bernard Twum Agyeman, Soumya Ranjan Sahoo, Xunyuan Yin, Jinfeng Liu   +4 more
wiley   +1 more source

Firefly algorithm based WSN-IoT security enhancement with machine learning for intrusion detection

Scientific Reports
A Wireless Sensor Network (WSN) aided by the Internet of Things (IoT) is a collaborative system of WSN systems and IoT networks are work to exchange, gather, and handle data.
M. Karthikeyan, D. Manimegalai, Karthikeyan RajaGopal   +2 more
doaj   +1 more source

Factorizations of Nonlinear Systems [PDF]

, 2000
In this chapter, we apply the L2 -gain concepts and techniques from Chaps. 3 and 8 to obtain some useful types of representations of nonlinear systems, different from the standard input-state-output representation.
openaire   +2 more sources

Neural Network Adaptive Control With Long Short‐Term Memory

International Journal of Adaptive Control and Signal Processing, EarlyView.
ABSTRACT In this study, we propose a novel adaptive control architecture that provides dramatically better transient response performance compared to conventional adaptive control methods. This is accomplished by the synergistic employment of a traditional adaptive neural network (ANN) controller and a long short‐term memory (LSTM) network.
Emirhan Inanc, Abdullah Habboush, Yigit Gurses, Yildiray Yildiz, Anuradha M. Annaswamy   +4 more
wiley   +1 more source

Qubit Neural Tree Network With Applications in Nonlinear System Modeling

IEEE Access, 2018
This paper proposed a newly quantum-inspired Qubit neural tree network with improved Qubit neuron, cross-layer connections and distinct phase operation functions for each neurons. A hybrid evolutionary algorithm that combines the modified gene expression
Feng Qi, Chao Chen
doaj   +1 more source