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- W2222732152 abstract "This paper presents the design and experimental validation of a new model-free data-driven iterative reference input tuning (IRIT) algorithm that solves a reference trajectory tracking problem as an optimization problem with control signal saturation constraints and control signal rate constraints. The IRIT algorithm design employs an experiment-based stochastic search algorithm to use the advantages of iterative learning control. The experimental results validate the IRIT algorithm applied to a non-linear aerodynamic position control system. The results prove that the IRIT algorithm offers the significant control system performance improvement by few iterations and experiments conducted on the real-world process and model-free parameter tuning." @default.
- W2222732152 created "2016-06-24" @default.
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- W2222732152 date "2015-10-19" @default.
- W2222732152 modified "2023-10-02" @default.
- W2222732152 title "Model-free constrained data-driven iterative reference input tuning algorithm with experimental validation" @default.
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- W2222732152 doi "https://doi.org/10.1080/03081079.2015.1072524" @default.
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