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<p>Piezo-actuated systems are widely utilized in high-precision positioning applications due to their high resolution and rapid response capabilities. However, inherent nonlinearities such as hysteresis and creep, together with parameter uncertainties and external disturbances, significantly degrade their performance. Existing model-based compensation and robust control strategies, including Sliding Mode Control (SMC), often suffer from modeling inaccuracies and chattering phenomena. To address these challenges, this paper proposes a novel Iterative Learning–Sliding Mode Control with Hysteresis (IL-SMCH) scheme. A proportional-derivative (PD)-type Iterative Learning Controller (ILC) is designed to reject repetitive disturbances and uncertain dynamics, while a second-order SMC ensures robust finite-time stability and reduces chattering effects. The Bouc-Wen model is employed to accurately capture the system’s hysteresis behavior. Stability and convergence are rigorously established through a composite Lyapunov-based energy function. Simulation results under step, sinusoidal, and triangular reference trajectories confirm that the tracking performance of IL-SMCH progressively improves with the number of iterations, achieving good results at 20 iterations. Comparative analysis demonstrates that IL-SMCH outperforms conventional PID, PID with Bouc-Wen compensation (PID-BW), SMC, and SMCH controllers by achieving lower mean absolute error (MAE), the ISE (Integral of Squared Error) and ITSE (Integral of Time-weighted Squared Error) eliminating overshoot, and significantly reducing chattering. These results validate the effectiveness of the proposed strategy for high-precision motion control in piezoelectric systems.</p>

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Enhanced position tracking for piezo-actuated systems using iterative learning-based sliding mode control with hysteresis

  • 期刊论文

  • 发表日期：

    2025年8月24日

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  • Nguyen Ngoc Son,
  • Tran Minh Chinh,
  • Nguyen Tien Dat

摘要

Piezo-actuated systems are widely utilized in high-precision positioning applications due to their high resolution and rapid response capabilities. However, inherent nonlinearities such as hysteresis and creep, together with parameter uncertainties and external disturbances, significantly degrade their performance. Existing model-based compensation and robust control strategies, including Sliding Mode Control (SMC), often suffer from modeling inaccuracies and chattering phenomena. To address these challenges, this paper proposes a novel Iterative Learning–Sliding Mode Control with Hysteresis (IL-SMCH) scheme. A proportional-derivative (PD)-type Iterative Learning Controller (ILC) is designed to reject repetitive disturbances and uncertain dynamics, while a second-order SMC ensures robust finite-time stability and reduces chattering effects. The Bouc-Wen model is employed to accurately capture the system’s hysteresis behavior. Stability and convergence are rigorously established through a composite Lyapunov-based energy function. Simulation results under step, sinusoidal, and triangular reference trajectories confirm that the tracking performance of IL-SMCH progressively improves with the number of iterations, achieving good results at 20 iterations. Comparative analysis demonstrates that IL-SMCH outperforms conventional PID, PID with Bouc-Wen compensation (PID-BW), SMC, and SMCH controllers by achieving lower mean absolute error (MAE), the ISE (Integral of Squared Error) and ITSE (Integral of Time-weighted Squared Error) eliminating overshoot, and significantly reducing chattering. These results validate the effectiveness of the proposed strategy for high-precision motion control in piezoelectric systems.