| Almost sure convergence of iterative learning control for stochastic systems |
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| 作者姓名： | 陈翰馥 |
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| 作者单位： | Institute of |
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| 基金项目： | This work was supported by the National Natural Science Foundation of China，by the Ministry of Science and Technology of China. |
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| 摘 要： | This paper proposes an iterative learning control (ILC) algorithm with the purpose of controling the output of a linear stochastic system presented in state space form to track a desired realizable trajectory. It is proved that the algorithm converges to the optimal one a.s. under the condition that the product input-output coupling matrices are full-column rank in addition to some assumptions on noises. No other knowledge about system matrices and covariance matrices is required.
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Almost sure convergence of iterative learning control for stochastic systems |
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| Chen?Hanfu.Almost sure convergence of iterative learning control for stochastic systems[J].Science in China(Information Sciences),2003,46(1):67-79. |
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| Authors: | Chen Hanfu |
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| Affiliation: | Institute of Systems Science, Academy of Mathematics and System Sciences, Chinese Academy of Sciences,Beijing 100080, China |
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| Abstract: | This paper proposes an iterative learning control (ILC) algorithm with the purpose of controling the output of a linear stochastic system presented in state space form to track a desired realizable trajectory. It is proved that the algorithm converges to the optimal one a.s. under the condition that the product input-output coupling matrices are full-column rank in addition to some assumptions on noises. No other knowledge about system matrices and covariance matrices is required. |
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| Keywords: | iterative learning control stochastic system a s convergence tracking stochastic approximation |
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