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Iterative learning control for MIMO second-order hyperbolic distributed parameter systems with uncertainties
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DOI：10.1186/s13662-016-0820-8.png)
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Abstract
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In this paper, we consider an iterative learning control (ILC) problem for a class of multiinput-multioutput (MIMO) second-order hyperbolic distributed parameter systems with uncertainties. A P-type ILC scheme is proposed in the iteration procedure for distributed systems with an initial deviation in the state. A convergence of tracking error with respect to the iteration index can be guaranteed in the sense of L-2 norm. Feasibility in theory of the iterative learning algorithm with difference method is proposed. Numerical simulation results are presented to illustrate the effectiveness of the proposed ILC approach.
Keywords:
iterative learning control
second-order hyperbolic distributed parameter systems
convergence
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