首页> 外文会议>International Conference on Advanced Robotics and Mechatronics >Parameter Identification Based on PSO Algorithm for Piezoelectric Actuating System with Rate-dependent Prandtl-Ishlinskii Hysteresis Modeling Method
【24h】

Parameter Identification Based on PSO Algorithm for Piezoelectric Actuating System with Rate-dependent Prandtl-Ishlinskii Hysteresis Modeling Method

机译:基于PSO算法的压电驱动系统参数识别Prandtl-Ishlinskii滞后建模

获取原文

摘要

Piezoelectric materials as a class of smart materials are widely used in precision machining, flexible manipulator and positioning systems with good features, such as positioning with high precision and great driving power. Actuators based on piezoelectric materials are becoming more important in the area of micro-operation especially in the micro-nano positioning stage. However, in the practical applications, some nonlinear characteristics of piezoelectric actuators, especially hysteretic nonlinearities, influence the positioning precision. It is necessary to characterize the hysteresis nonlinearities to facilitate the controller design improving the driving precision. In this paper, based on the rate-dependent Prandtl-Ishlinskii (RDPI) model, a Particle Swarm Optimization (PSO) algorithm is proposed in the parameters identification procedure to optimize the hysteresis modeling precision. To show the effectiveness of the proposed identification method, the outputs of the identified model are compared with the actual measurement data from the piezoelectric actuating platform under the different input frequencies.
机译:压电材料是一类智能材料,广泛用于精密加工,柔性机械手和定位系统,具有定位精度高,驱动力强等特点。在微操作领域,特别是在微纳米定位阶段,基于压电材料的执行器变得越来越重要。但是,在实际应用中,压电致动器的某些非线性特性,特别是磁滞非线性,会影响定位精度。必须描述磁滞非线性特性,以利于控制器设计提高驱动精度。本文基于速率依赖的Prandtl-Ishlinskii(RDPI)模型,在参数辨识过程中提出了一种粒子群优化(PSO)算法,以优化磁滞建模精度。为了显示所提出的识别方法的有效性,将所识别模型的输出与在不同输入频率下来自压电致动平台的实际测量数据进行比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号