Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/1722
Title: | Direct Adaptive Control of a Flexible Robot using Reinforcement Learning |
Authors: | Subudhi, B D Pradhan, Santanu Kumar |
Keywords: | Flexible-Link Manipulator Actor Critic based Adaptive dynamic programming Variable Tip Mass |
Issue Date: | Dec-2010 |
Citation: | proceedings of the IEEE sponsored International Conference on Industrial Electronics, Control & Robotics (IECR), 2010 ,NIT Rourkela, Rourkela , pp.129-136, 27-29 Dec. 2010 |
Abstract: | This paper proposes a new adaptive control using the concept of reinforcement learning to address adaptivity for varied payload conditions for a two-link flexible manipulator (TLFM). The application of reinforcement learning has been implemented using a method called adaptive dynamic programming. Decentralized controllers for the decoupled system have been also designed using LQR technique. Then the reinforcement learning is used to tune the gains of the optimal control to adapt in terms of different payload to the manipulator end effecter. Simulation results show that proposed controller provides better end point tracking then LQR fixed gain controller. |
Description: | Copyright belongs to proceeding publisher |
URI: | http://hdl.handle.net/2080/1722 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2010_Direct Adaptive Control of a Flexible Robot using.pdf | 983.37 kB | Adobe PDF | View/Open |
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