A deep reinforcement learning-based optimization method for vibration suppression of articulated robots-Reference-Cited by-同舟云学术

A deep reinforcement learning-based optimization method for vibration suppression of articulated robots

Published:2022-05-03 Issue: Volume: Page:1-18
ISSN:0305-215X
Container-title:Engineering Optimization
language:en
Short-container-title:Engineering Optimization

Author:

Zhang Tie¹,Chu Hubo¹,Zou Yanbiao¹,Liu Tao¹

Affiliation:

1. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, People’s Republic of China

Funder

Science and Technology Planning Project of Guangdong Province

Publisher

Informa UK Limited

Subject

Applied Mathematics,Industrial and Manufacturing Engineering,Management Science and Operations Research,Control and Optimization,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2022.2065482

Reference26 articles.

1. Adaptive output-based command shaping for sway control of a 3D overhead crane with payload hoisting and wind disturbance

2. FIR filters for online trajectory planning with time- and frequency-domain specifications

3. Intelligent Backstepping System to Increase Input Shaping Performance in Suppressing Residual Vibration of a Flexible-Joint Robot Manipulator

4. Reinforcement Learning-Based Control of Nonlinear Systems Using Lyapunov Stability Concept and Fuzzy Reward Scheme

5. Neural Network Control of a Two-Link Flexible Robotic Manipulator Using Assumed Mode Method

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