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<p>This work proposes a state-transformation‐based adaptive boundary control framework with a novel prescribed performance function and a variable-frequency Nussbaum function to handle unknown control directions while suppressing vibrations. The prescribed performance function is designed with zero first- and second-order derivatives at initiation, ensuring smooth transients and reduced control effort. A Switching Dynamic Event-Triggered Mechanism (SDETM) balances performance and communication load, achieving a 47% reduction in control updates compared to continuous-update schemes. Lyapunov analysis and Barbalat’s lemma guarantee boundedness of all closed-loop signals and asymptotic vibration attenuation. Simulations demonstrate that the proposed approach maintains tracking errors within predefined bounds under actuator faults, dead-zone nonlinearities, and external disturbances, outperforming conventional BLF-based methods in stability, robustness, and communication efficiency.</p>

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Vibration adaptive control for flexible manipulators with unknown directions

  • 期刊论文

  • 发表日期：

    2026年3月30日

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  • Mostafa Jalalnezhad

摘要

This work proposes a state-transformation‐based adaptive boundary control framework with a novel prescribed performance function and a variable-frequency Nussbaum function to handle unknown control directions while suppressing vibrations. The prescribed performance function is designed with zero first- and second-order derivatives at initiation, ensuring smooth transients and reduced control effort. A Switching Dynamic Event-Triggered Mechanism (SDETM) balances performance and communication load, achieving a 47% reduction in control updates compared to continuous-update schemes. Lyapunov analysis and Barbalat’s lemma guarantee boundedness of all closed-loop signals and asymptotic vibration attenuation. Simulations demonstrate that the proposed approach maintains tracking errors within predefined bounds under actuator faults, dead-zone nonlinearities, and external disturbances, outperforming conventional BLF-based methods in stability, robustness, and communication efficiency.