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Abstract
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Article Information:
Reinforcement Learning with FCMAC for TRMS Control
Jih-Gau Juang and Yi-Chong Chiang
Corresponding Author: Jih-Gau Juang
Submitted: July 09, 2012
Accepted: July 31, 2012
Published: February 01, 2013 |
Abstract:
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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.
Key words: Fuzzy CMAC, PID control, reinforcement learning, twin rotor MIMO system, , ,
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Abstract
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Cite this Reference:
Jih-Gau Juang and Yi-Chong Chiang, . Reinforcement Learning with FCMAC for TRMS Control. Research Journal of Applied Sciences, Engineering and Technology, (04): 1383-1389.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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