Oct 10, 2022 · This paper proposes a novel adaptive law for the critic network in the RL framework to address this problem.

This paper proposes a novel adaptive law for the critic network in the RL framework to address this problem.

Recent years, there has been an increasing interest in the application of reinforcement learning (RL) to nonlinear system control.

Oct 22, 2024 · This paper estimates an off-policy integral reinforcement learning (IRL) algorithm to obtain the optimal tracking control of unknown chaotic ...

This article presents an optimal online RL tracking control framework for discrete‐time (DT) systems, which does not impose any restrictive assumptions of ...

Bibliographic details on Optimal tracking control of mechatronic servo system using integral reinforcement learning.

Dec 19, 2022 · This paper aims at the characteristics of nonlinear, time-varying and parameter coupling in a hydraulic servo system.

Mar 29, 2023 · This paper introduces an optimal tracking controller for robot manipulators with asymmetrically saturated torques and partially - unknown ...

A reinforcement learning (RL) based adaptive dynamic programming (ADP) is developed to learn the approximate optimal stabilization input of the servo ...

Dec 23, 2024 · The results indicate that RL controllers can outperform PID controllers in terms of accuracy and response time for DC motor speed control, ...