Learning from adaptive neural network output feedback control of a unicycle-type mobile robot
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- 作者：Wei Zeng ; zw0597@126.com" class="auth_mail" title="E-mail the corresponding author ; Qinghui Wang ; Fenglin Liu ; Ying Wang
- 关键词：Deterministic learning ; Unicycle-type mobile robots ; Adaptive output feedback ; RBF neural network ; High-gain observer ; Learning control
- 刊名：ISA Transactions
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：61
- 期：Complete
- 页码：337-347
- 全文大小：4362 K
文摘
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We present a new method for output feedback control of unicycle-type mobile robots.
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The unknown system dynamics can be learned by using RBF neural networks.
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High-gain observers are designed to estimate the unmeasurable system states.
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Stability of the robot system and convergence of tracking errors are guaranteed.
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The learned knowledge of system dynamics can be recalled for similar control tasks.