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Volume 3 Issue 1
Jan.  2016

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2016  >  3(1): 59-67
Dong Shen and Yun Xu, "Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information," IEEE/CAA J. of Autom. Sinica, vol. 3, no. 1, pp. 59-67, 2016.
Citation: Dong Shen and Yun Xu, "Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information," IEEE/CAA J. of Autom. Sinica, vol. 3, no. 1, pp. 59-67, 2016.
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Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information

  • College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China

Funds:

This work was supported by National Natural Science Foundation of China (61304085) and Beijing Natural Science Foundation (4152040).

    Abstract
  • An iterative learning control (ILC) algorithm using quantized error information is given in this paper for both linear and nonlinear discrete-time systems with stochastic noises. A logarithmic quantizer is used to guarantee an adaptive improvement in tracking performance. A decreasing learning gain is introduced into the algorithm to suppress the effects of stochastic noises and quantization errors. The input sequence is proved to converge strictly to the optimal input under the given index. Illustrative simulations are given to verify the theoretical analysis.

     

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