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<p>This paper proposes robust indirect adaptive control (RIAC) scheme to control acoustically levitated object using standing wave-based acoustic levitation system. Acoustic levitation serves as the novel mean to manipulate objects of small sizes and of different morphological shapes comprising rigid and malleable objects. RIAC features fixed-time levitation tracking control law with indirect nonlinear feedback compensation to control the levitation level. The proposed algorithm was evaluated in the simulation environment of MATLAB/Simulink under the presence of bounded disturbances and nominal condition. It was then compared with model predictive control (MPC) using the performance indices integral absolute error (IAE), integral of absolute control effort (IACE), and integral square error (ISE) to assess its performance in terms of tracking error, stability and control effort. RIAC achieves an IAE of 0.1205 as compared to MPC which achieves an IAE of 5.066 in the presence of bounded disturbances. The superior performance exemplified by RIAC in this paper, proves that the proposed algorithm can be implemented on a non-contact manipulator where, the pick-and-place operation can be performed seamlessly without contact. This paves a way for industrial application encompassing industries such as semiconductor production, pharmaceutical, chemical process and others.</p>

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Robust Indirect Adaptive Control of Acoustic Levitation Standing Waves-based Scheme for Robotic Non-contact Manipulation Applications

  • 期刊论文

  • 发表日期：

    2025年6月11日

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  • Ibrahim Ismael Ibrahim Al-Nuaimi,
  • Muhammad Nasiruddin Mahyuddin

摘要

This paper proposes robust indirect adaptive control (RIAC) scheme to control acoustically levitated object using standing wave-based acoustic levitation system. Acoustic levitation serves as the novel mean to manipulate objects of small sizes and of different morphological shapes comprising rigid and malleable objects. RIAC features fixed-time levitation tracking control law with indirect nonlinear feedback compensation to control the levitation level. The proposed algorithm was evaluated in the simulation environment of MATLAB/Simulink under the presence of bounded disturbances and nominal condition. It was then compared with model predictive control (MPC) using the performance indices integral absolute error (IAE), integral of absolute control effort (IACE), and integral square error (ISE) to assess its performance in terms of tracking error, stability and control effort. RIAC achieves an IAE of 0.1205 as compared to MPC which achieves an IAE of 5.066 in the presence of bounded disturbances. The superior performance exemplified by RIAC in this paper, proves that the proposed algorithm can be implemented on a non-contact manipulator where, the pick-and-place operation can be performed seamlessly without contact. This paves a way for industrial application encompassing industries such as semiconductor production, pharmaceutical, chemical process and others.