基于傅立叶级数的摆式胶囊驱动控制优化算法:计算与实验综合研究

Sandra Zarychta, Marek Balcerzak, Katarzyna Wojdalska, Rafał Dolny, Jerzy Wojewoda
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引用次数: 0

摘要

摆锤驱动系统是对振动撞击装置的一种显著改进,用摆锤取代了传统的质量-弹簧振荡器。由于方向动力学、摆锤运动以及设计装置与底层表面之间的接触力的相互作用,此类系统表现出错综复杂的行为。本文深入探讨了基于傅立叶级数的贪婪算法在摆式胶囊驱动器控制优化中的应用,该算法在内窥镜胶囊机器人、管道检测和密闭空间救援行动等多种应用场景中都具有潜力。重点放在涉及原型开发的实验研究上,以验证系统与之前计算模拟的有效性。实证研究结果与数值研究结果非常吻合(损失小于 2%),表明摆式胶囊驱动装置能够在三次谐波和六次谐波中分别达到 2.48 厘米/秒和 2.58 厘米/秒的平均速度。高质量的信号跟踪精度加强了这些结果,证明了在运动过程中对潜在干扰的适应能力。作者认为基于傅立叶级数的控制优化方法是确保提高非连续系统运动性能的重要一步,它能有效处理干摩擦产生的非线性问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fourier series-based algorithm for control optimization in pendulum capsule drive: an integrated computational and experimental study
Pendulum-driven systems have emerged as a notable modification of vibro-impact mechanisms, replacing the conventional mass-on-spring oscillator with a pendulum. Such systems exhibit intricate behavior resulting from the interplay of directional dynamics, pendulum motion, and contact forces between the designed device and the underlying surface. This paper delves into the application of a Fourier series-based greedy algorithm for control optimization in pendulum capsule drives, which hold potential for diverse scenarios, including endoscopy capsule robots, pipeline inspection, and rescue operations in confined spaces. The emphasis is placed on experimental studies involving prototype development to validate the system's efficacy with previous computational simulations. Empirical findings closely align (<2% loss) with numerical investigations, showcasing the pendulum capsule drive's ability to achieve average speeds of 2.48 cm/s and 2.58 cm/s for three and six harmonics, respectively. These results are reinforced by high-quality signal-tracking accuracy, which demonstrates resilience against potential disturbances during motion. The authors envision the Fourier series-based control optimization method as a significant step towards ensuring enhanced locomotion performance in discontinuous systems, effectively handling the non-linearities arising from dry friction.
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