Research Article | OPEN ACCESS
Reinforcement Learning with FCMAC for TRMS Control
Jih-Gau Juang and Yi-Chong Chiang
Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung, 20224, Taiwan
Research Journal of Applied Sciences, Engineering and Technology 2013 4:1383-1389
Received: July 09, 2012 | Accepted: July 31, 2012 | Published: February 01, 2013
Abstract
This study proposes an intelligent control scheme that integrate reinforcement learning in Fuzzy CMAC (FCMAC) for a Twin Rotor Multi-input and multi-output System (TRMS). In the control design, fuzzy CMAC controller is utilized to compensate for PID control signal and the reinforcement learning refines the compensation to the control signal. CMAC with fuzzy system has better performance than the conventional CMAC in TRMS attitude tracking control. With reinforcement learning, the proposed control scheme provides even better performance and control for the TRMS.
Keywords:
Fuzzy CMAC, PID control, reinforcement learning, twin rotor MIMO system,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
|
|
 |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
 |
| Information |
|
|
|
|
| Sales & Services |
|
|
|
|
