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<p>Iterative learning preview control (ILPC) is a highly effective control methodology for tracking previewed reference signals. This study applies the preview control theory to iterative learning control systems and proposes the fuzzy ILPC scheme. Firstly, two kinds of fuzzy ILPC laws are considered for previewed reference signals. Next, an augmented error model is constructed, so that the design of fuzzy ILPC laws is turned into a feedback control task of the augmented model. Then, the conditions for asymptotic stability are derived by the Lyapunov function with linear matrix inequality conditions, thereby designing the fuzzy ILPC laws. Finally, an example illustrates the validity of the proposed control scheme in T–S fuzzy systems.</p>

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A Fuzzy Iterative Learning Preview Controller for Takagi–Sugeno Fuzzy Systems

  • 期刊论文

  • 发表日期：

    2025年4月11日

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  • Li Li,
  • Jiang Wu,
  • Yanrong Lu

摘要

Iterative learning preview control (ILPC) is a highly effective control methodology for tracking previewed reference signals. This study applies the preview control theory to iterative learning control systems and proposes the fuzzy ILPC scheme. Firstly, two kinds of fuzzy ILPC laws are considered for previewed reference signals. Next, an augmented error model is constructed, so that the design of fuzzy ILPC laws is turned into a feedback control task of the augmented model. Then, the conditions for asymptotic stability are derived by the Lyapunov function with linear matrix inequality conditions, thereby designing the fuzzy ILPC laws. Finally, an example illustrates the validity of the proposed control scheme in T–S fuzzy systems.