Machine Learning-Based Multiagent Control for a Bunch of Flexible Robots
In this paper, two novel methodologies of employing machine learning (here, the type-2 fuzzy system) are presented to control a multiagent system in which the agents are flexible joint robots. In the previous methods, the static mode controller has been investigated, which has little flexibility and...
Saved in:
Main Authors: | Jun Wang, Jiali Zhang, Jafar Tavoosi, Mohammadamin Shirkhani |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2024-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2024/1330458 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive Optimal Terminal Sliding Mode Control for T-S Fuzzy-Based Nonlinear Systems
by: Farzad Soltanian, et al.
Published: (2024-01-01) -
Nonlinear Control and Synchronization with Time Delays of Multiagent Robotic Systems
by: Yassine Bouteraa, et al.
Published: (2011-01-01) -
UAV Intelligent Control Based on Machine Vision and Multiagent Decision-Making
by: Zishan Huang
Published: (2022-01-01) -
Evaluating the Smoothness of the Washed Fabric after Laundry with the Washing Machine Based on a New Type-2 Fuzzy Neural Network
by: Mir Saeid Hesarian, et al.
Published: (2022-01-01) -
MARS: An Educational Environment for Multiagent Robot Simulations
by: Marco Casini, et al.
Published: (2016-01-01)