A Q-Learning-Based Parameters Adaptive Algorithm for Formation Tracking Control of Multi-Mobile Robot Systems
This paper proposes an adaptive formation tracking control algorithm optimized by Q-learning scheme for multiple mobile robots. In order to handle the model uncertainties and external disturbances, a desired linear extended state observer is designed to develop an adaptive formation tracking control...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
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Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2022/5093277 |
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