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<p>This paper presents a novel adaptive neural control using an inverse Bouc-Wen model (ANC-IBW) for precise trajectory tracking of piezoelectric actuators (PEA). The approach includes an improved differential evolution algorithm (IDE) for identifying Bouc-Wen model parameters to design a feedforward compensator, which effectively captures the hysteresis in PEA systems. An adaptive control component based on the radial basis function neural network (RBFNN) model is designed to handle parameter uncertainties and disturbances, and the switching control component is for the system’s stability. The stability is analyzed using Lyapunov theory and Barbalat’s lemma. To assess the effectiveness of the proposed control, it is compared to traditional PID control, feedforward control based on the inverse Bouc-Wen model (IBW), and a hybrid PID-IBW control. Experimental results, obtained using a Thorlabs PZS001 actuator and a TMS320F28379D kit, demonstrate that ANC-IBW significantly outperforms those controllers. The tracking error achieved a 2–5 times reduction compared to the PID, and IBW controls, while also showing a slight improvement compared with the PID-IBW control.</p>

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Trajectory tracking of piezoelectric actuators using adaptive neural control with inverse Bouc–Wen model

  • 期刊论文

  • 发表日期：

    2026年7月17日

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  • Nguyen Ngoc Son,
  • Kien Van Cao,
  • Tran Minh Chinh

摘要

This paper presents a novel adaptive neural control using an inverse Bouc-Wen model (ANC-IBW) for precise trajectory tracking of piezoelectric actuators (PEA). The approach includes an improved differential evolution algorithm (IDE) for identifying Bouc-Wen model parameters to design a feedforward compensator, which effectively captures the hysteresis in PEA systems. An adaptive control component based on the radial basis function neural network (RBFNN) model is designed to handle parameter uncertainties and disturbances, and the switching control component is for the system’s stability. The stability is analyzed using Lyapunov theory and Barbalat’s lemma. To assess the effectiveness of the proposed control, it is compared to traditional PID control, feedforward control based on the inverse Bouc-Wen model (IBW), and a hybrid PID-IBW control. Experimental results, obtained using a Thorlabs PZS001 actuator and a TMS320F28379D kit, demonstrate that ANC-IBW significantly outperforms those controllers. The tracking error achieved a 2–5 times reduction compared to the PID, and IBW controls, while also showing a slight improvement compared with the PID-IBW control.