用分数阶微分方程+粒子群优化，精准建模软致动器动态行为
Fractional-order Modeling for Nonlinear Soft Actuators via Particle Swarm Optimization
- 采用分数阶微分方程描述软材料非线性特性，提升建模精度
- 通过粒子群优化从实验数据直接估算参数，无需材料数据库
- 数据高效且不依赖先验模型，适合复杂软体机器人设计
由于软气动致动器具有高度非线性和柔顺特性，实现高精度建模仍是一大挑战。本文提出一种基于分数阶微分方程（FODEs）的创新建模框架，以准确捕捉软材料的动态行为。分数阶模型中的未知参数通过粒子群优化（PSO）识别，可直接从实验数据中估计，无需依赖预设材料数据库或经验本构关系。所提方法有效表征了软致动器固有的复杂变形现象。实验结果验证了该模型的准确性与鲁棒性，其预测性能优于传统建模技术。该框架提供了数据高效且数据库无关的软致动器建模方案，推动了软体机器人系统设计的精度与适应性。
原文摘要 · Abstract (English)
Modeling soft pneumatic actuators with high precision remains a fundamental challenge due to their highly nonlinear and compliant characteristics. This paper proposes an innovative modeling framework based on fractional-order differential equations (FODEs) to accurately capture the dynamic behavior of soft materials. The unknown parameters within the fractional-order model are identified using particle swarm optimization (PSO), enabling parameter estimation directly from experimental data without reliance on pre-established material databases or empirical constitutive laws. The proposed approach effectively represents the complex deformation phenomena inherent in soft actuators. Experimental results validate the accuracy and robustness of the developed model, demonstrating improvement in predictive performance compared to conventional modeling techniques. The presented framework provides a data-efficient and database-independent solution for soft actuator modeling, advancing the precision and adaptability of soft robotic system design.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。