经纱张力的神经非奇异积分快速终端滑模控制  

Neural Nonsingular Integral Fast Terminal Sliding Mode Control for Warp Tension

作　　者：付茂文 沈丹峰[1] 赵刚 尚国飞 柏顺伟 FU Maowen;SHEN Danfeng;ZHAO Gang;SHANG Guofei;BAI Shunwei(School of Mechanical and Electrical Engineering,Xi'an Polytechnic University,Xi'an 710048,China;Shaanxi Changling Textile Mechanical&Electronic Technological Co.,Ltd.,Baoji 721013,Shaanxi,China)

机构地区：[1]西安工程大学机电工程学院,西安710048 [2]陕西长岭纺织机电科技有限公司,陕西宝鸡721013

出　　处：《机械科学与技术》2024年第9期1600-1607,共8页Mechanical Science and Technology for Aerospace Engineering

基　　金：国家自然科学基金项目(51805402)。

摘　　要：为减小织机长片段经纱张力波动,提高张力控制性能,提出神经非奇异积分快速终端滑模控制(RBF-NIFTSMC)方法。通过对送经系统的受力分析,建立了织机的时变张力控制模型,根据系统存在时变数学模型、未建模动力学和外部干扰未知等特点,设计了一种非奇异积分快速终端滑模控制方法。该控制器可在短时间内到达滑模面,无奇异问题,利用NIFTSMC理论自适应估计未知不确定性,并最终由李雅普诺夫理论证明稳定性。为进一步提高滑模控制性能,将滑模面和变步长神经网络相融合,实现时变滑模面,神经网络的参数由改进天鹰优化(AO)算法优化得到,最终通过仿真实验结果证明所提出的控制方法的有效性。In order to reduce the tension fluctuation of long segment warp and improve the tension control performance,A neural nonsingular integral fast terminal sliding model control(RBF-NIFTSMC)method was proposed.Through the force analysis of the let off system,the time-varying tension control model of the loom was first established.According to the characteristics of the system,such as time-varying mathematical model,unmodeled dynamics and unknown external interference,a nonsingular integral fast terminal synovial control method is designed.The controller can reach the sliding mode surface in a short time without singular problems.The unknown uncertainty is adaptively estimated by using NIFTSMC theory,and the stability was then proved by Lyapunov theory.In order to further improve the sliding mode control performance,the sliding mode surface and variable step size neural network were fused to realize the time-varying sliding mode surface.The parameters of the neural network were optimized by the improved Aquila optimization algorithm.Finally,the simulation results show the effectiveness of the proposed control method.

关 键 词：张力 送经系统 滑模控制 神经网络 天鹰优化算法 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TS103.7[自动化与计算机技术—控制科学与工程]