Adaptive-critic design for decentralized event-triggered control of constrained nonlinear interconnected systems within an identifier-critic framework
This article studies the decentralized event-triggered control problem for a class of
constrained nonlinear interconnected systems. By assigning a specific cost function for each …
constrained nonlinear interconnected systems. By assigning a specific cost function for each …
NN reinforcement learning adaptive control for a class of nonstrict-feedback discrete-time systems
W Bai, T Li, S Tong - IEEE Transactions on Cybernetics, 2020 - ieeexplore.ieee.org
This article investigates an adaptive reinforcement learning (RL) optimal control design
problem for a class of nonstrict-feedback discrete-time systems. Based on the neural …
problem for a class of nonstrict-feedback discrete-time systems. Based on the neural …
Artificial intelligence methods in safe ship control based on marine environment remote sensing
J Lisowski - Remote Sensing, 2022 - mdpi.com
This article presents a combination of remote sensing, an artificial neural network, and game
theory to synthesize a system for safe ship traffic management at sea. Serial data …
theory to synthesize a system for safe ship traffic management at sea. Serial data …
Cooperative game-based approximate optimal control of modular robot manipulators for human–robot collaboration
Major challenges of controlling human–robot collaboration (HRC)-oriented modular robot
manipulators (MRMs) include the estimation of human motion intention while cooperating …
manipulators (MRMs) include the estimation of human motion intention while cooperating …
Dynamic event-triggering neural learning control for partially unknown nonlinear systems
This article presents an event-sampled integral reinforcement learning algorithm for partially
unknown nonlinear systems using a novel dynamic event-triggering strategy. This is a novel …
unknown nonlinear systems using a novel dynamic event-triggering strategy. This is a novel …
Data-driven inverse reinforcement learning control for linear multiplayer games
This article proposes a data-driven inverse reinforcement learning (RL) control algorithm for
nonzero-sum multiplayer games in linear continuous-time differential dynamical systems …
nonzero-sum multiplayer games in linear continuous-time differential dynamical systems …
Adaptive learning and sampled-control for nonlinear game systems using dynamic event-triggering strategy
Static event-triggering-based control problems have been investigated when implementing
adaptive dynamic programming algorithms. The related triggering rules are only current …
adaptive dynamic programming algorithms. The related triggering rules are only current …
Input–output data-based output antisynchronization control of multiagent systems using reinforcement learning approach
This article investigates an output antisynchronization problem of multiagent systems by
using an input-output data-based reinforcement learning approach. Till now, most of the …
using an input-output data-based reinforcement learning approach. Till now, most of the …
Event-triggered adaptive neural network tracking control for uncertain systems with unknown input saturation based on command filters
J Liu, QG Wang, J Yu - IEEE Transactions on Neural Networks …, 2022 - ieeexplore.ieee.org
This brief presents a modified event-triggered command filter backstep** tracking control
scheme for a class of uncertain nonlinear systems with unknown input saturation based on …
scheme for a class of uncertain nonlinear systems with unknown input saturation based on …