Results 61 to 70 of about 73,043 (272)

Learning Transformed Dynamics for Efficient Control Purposes

Mathematics
Learning linear and nonlinear dynamical systems from available data is a timely topic in scientific machine learning. Learning must be performed while enforcing the numerical stability of the learned model, the existing knowledge within an informed or ...
Chady Ghnatios, Joel Mouterde, Jerome Tomezyk, Joaquim Da Silva, Francisco Chinesta   +4 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

An Adaptive Human Pilot Model With Reaction Time Delay for Enhanced Adaptive Control in Piloted Systems

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces an adaptive human pilot model that captures pilot time‐delay effects in adaptive control systems. The model enables the prediction of pilot–controller interactions, facilitating safer integration and improved design of adaptive controllers for piloted applications.
Abdullah Habboush, Yildiray Yildiz
wiley   +1 more source

SMC-Based, Stability-Guided Deep Reinforcement Learning for Control of Uncertain Nonlinear Dynamic Systems

IEEE Access
This paper presents a novel control framework that integrates the stability insights of traditional control with reinforcement learning (RL) to tackle uncertain nonlinear dynamic systems.
Mahya Ramezani, M. Amin Alandihallaj, Andreas M. Hein, Holger Voos   +3 more
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Fine-Tuning Quadcopter Control Parameters via Deep Actor-Critic Learning Framework: An Exploration of Nonlinear Stability Analysis and Intelligent Gain Tuning

IEEE Access
Quadcopters have underactuated, nonlinear, and coupled dynamics, making their control a challenging endeavor. However, PID controllers have exhibited remarkable performance for such systems in a variety of circumstances, including obstacle avoidance ...
Hassan Moin, Umer Hameed Shah, Muhammad Jawad Khan, Hasan Sajid   +3 more
doaj   +1 more source

Design performance of lead and lag compensator using OPAMP and root locus approach through simulation tool

ITEGAM-JETIA, 2020
The design objective behind lead and lag compensator is to meet the relative stability as well as to meet desired performance. Both in time domain or frequency domain, the compensator design can be carried out.
Badri Narayan Mohapatra, Jijnyasa Joshi
doaj   +1 more source

Recent Advancements in Bulk Processing of Rare‐Earth‐Free Hard Magnetic Materials and Related Multiscale Simulations

Advanced Engineering Materials, EarlyView.
This article provides an overview of recent advancements in bulk processing of rare‐earth‐free hard magnetic materials. It also addresses related simulation approaches at different scales. The research on rare‐earth‐free magnetic materials has increased significantly in recent years, driven by supply chain issues, environmental and social concerns, and
Daniel Scheiber, Andrea Bachmaier
wiley   +1 more source

Optimal Control Based on Reinforcement Learning for Flexible High-Rise Buildings with Time-Varying Actuator Failures and Asymmetric State Constraints

Buildings
This study centers on the vibration suppression of high-rise building systems under extreme conditions, exploring a reinforcement learning (RL)-based vibration control strategy for flexible building systems with time-varying faults and asymmetric state ...
Min Li, Rui Xie
doaj   +1 more source

Game Theory-Inspired Evolutionary Algorithm for Global Optimization

Algorithms, 2017
Many approaches that model specific intelligent behaviors perform excellently in solving complex optimization problems. Game theory is widely recognized as an important tool in many fields.
Guanci Yang
doaj   +1 more source