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Control Theory for Distributed Parameter Systems and Applications
Thank you for posting a review! We value your input. In this paper, a class of parabolic distributed parameter system with coefficient uncertain but bounded is studied by using iterative learning algorithm with adjustable forgetting factor. The sufficient conditions of convergence L2-norm of the tracking error are given.
The theoretical analysis and simulation results show that the proposed ILC algorithm is effective. We will look forward to more learning algorithms applied to the distributed parameter systems in the future. The authors declare that there is no conflict of interests regarding the publication of this paper.
An Observation Theory for Distributed-Parameter Systems
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