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<p>In industrial applications, the use of multiple robotic manipulators for collaborative tasks significantly enhances operational flexibility and agility. However, as the number of robotic arms increases, so do the system’s complexity and nonlinearity, leading to uncertainties and unmodeled dynamics. Moreover, external factors such as disturbances can further degrade system performance. This study focuses on developing a robust adaptive control strategy for a robotic system composed of multiple cooperative arms carrying an object. Specifically, it introduces the use of <i>q</i>-Szasz–Schurer operators as uncertainty approximators. To the best of the authors’ knowledge, this is the first instance where these operators have been employed adaptively, as no prior research has provided adaptation rules for <i>q</i>-Szasz–Schurer operators. These powerful mathematical tools approximate system uncertainties, including unmodeled dynamics and external disturbances. Adaptive laws, derived through stability analysis, are used to adjust the coefficients of the <i>q</i>-Szasz–Schurer operators. The Lyapunov direct method ensures that all force and position tracking errors are uniformly ultimately bounded (UUB). The proposed controller/approximator is evaluated on a two-arm robotic system tasked with cooperative object manipulation, demonstrating its effectiveness. The numerical simulation results are also compared with an advanced approximation method, highlighting the accuracy and effectiveness of the proposed controller design. Both approximators yield almost identical results, with the exception that the <i>q</i>-Szasz–Schurer-based controller has a lower computational load compared to the RBFNN-based controller.</p>

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Coordinated manipulation and robust adaptive object handling by multiple manipulators, relying on the q-Szasz–Schurer operators as uncertainty approximator

  • 期刊论文

  • 发表日期：

    2025年1月31日

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  • Alireza Izadbakhsh

摘要

In industrial applications, the use of multiple robotic manipulators for collaborative tasks significantly enhances operational flexibility and agility. However, as the number of robotic arms increases, so do the system’s complexity and nonlinearity, leading to uncertainties and unmodeled dynamics. Moreover, external factors such as disturbances can further degrade system performance. This study focuses on developing a robust adaptive control strategy for a robotic system composed of multiple cooperative arms carrying an object. Specifically, it introduces the use of q-Szasz–Schurer operators as uncertainty approximators. To the best of the authors’ knowledge, this is the first instance where these operators have been employed adaptively, as no prior research has provided adaptation rules for q-Szasz–Schurer operators. These powerful mathematical tools approximate system uncertainties, including unmodeled dynamics and external disturbances. Adaptive laws, derived through stability analysis, are used to adjust the coefficients of the q-Szasz–Schurer operators. The Lyapunov direct method ensures that all force and position tracking errors are uniformly ultimately bounded (UUB). The proposed controller/approximator is evaluated on a two-arm robotic system tasked with cooperative object manipulation, demonstrating its effectiveness. The numerical simulation results are also compared with an advanced approximation method, highlighting the accuracy and effectiveness of the proposed controller design. Both approximators yield almost identical results, with the exception that the q-Szasz–Schurer-based controller has a lower computational load compared to the RBFNN-based controller.