Fuzzy-Based Adaptive Reliable Motion Control of a Piezoelectric Nanopositioning System

被引:5
|
作者
Chen, Liheng [1 ,2 ]
Xu, Qingsong [1 ]
机构
[1] Univ Macau, Fac Sci & Technol, Dept Electromech Engn, Macau, Peoples R China
[2] Harbin Engn Univ, Coll Intelligent Syst Sci & Engn, Harbin 150001, Peoples R China
基金
中国国家自然科学基金;
关键词
Nanopositioning; Hysteresis; Reliability; Couplings; Degradation; Tracking; Piezoelectric actuators; Adaptive fuzzy control; motion control; nanopositioning; piezoelectric actuator; reliable control; TRACKING CONTROL; STAGE;
D O I
10.1109/TFUZZ.2024.3399115
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The nonlinearity and cross-axis coupling of piezo-driven multiple-degree-of-freedom nanopositioning systems impose challenges to achieving precise and reliable motion control. This article develops a new adaptive reliable control approach for a two-degree-of-freedom piezoelectric nanopositioning system utilizing a fuzzy backstepping strategy. First, a virtual tracking model is constructed to address the stabilization problem via a system transformation method. Then, a fuzzy logic system model is introduced to mitigate the effects of hysteresis and unmodeled high-order nonlinearity. To obtain high-precision motion tracking with high reliability, the approximation of the unknown piezoelectric actuator's efficiency factor is injected into the reliable controller of nanopositioning systems. Furthermore, an adaptive mechanism based on tracking errors is designed to adjust control parameters automatically to improve the robustness to unknown perturbations. Simulation and practical experiment examples are presented to show the effectiveness and potential of the developed fuzzy reliable nanopositioning control method over existing control approaches.
引用
收藏
页码:4413 / 4425
页数:13
相关论文
共 50 条
  • [1] Laguerre Based Adaptive Control of Piezoelectric Actuator for Nanopositioning
    Wang, Yigang
    Chu, Kevin C.
    Chang, Herrick L.
    Tsao, Tsu-Chin
    49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2010, : 3712 - 3717
  • [2] Adaptive fuzzy-based motion generation and control of mobile under-actuated manipulators
    Li, Zhijun
    Yang, Chenguang
    Su, Chun-Yi
    Ye, Wenjun
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2014, 30 : 86 - 95
  • [3] Neural Networks Based Learning Control for a Piezoelectric Nanopositioning System
    Kong, Linghuan
    Li, Dan
    Zou, Jianxiao
    He, Wei
    IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2020, 25 (06) : 2904 - 2914
  • [4] Precision Motion Control of Piezoelectric Nanopositioning Stage With Chattering-Free Adaptive Sliding Mode Control
    Xu, Qingsong
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2017, 14 (01) : 238 - 248
  • [5] Fuzzy-based adaptive bandwidth control for loss guarantees
    Siripongwutikorn, P
    Banerjee, S
    Tipper, D
    IEEE TRANSACTIONS ON NEURAL NETWORKS, 2005, 16 (05): : 1147 - 1162
  • [6] Adaptive PI-Based Sliding Mode Control for Nanopositioning of Piezoelectric Actuators
    Li, Jin
    Yang, Liu
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2014, 2014
  • [7] Fuzzy-based Adaptive Motion Control of a Virtual iCub Robot in Human-Robot-Interaction
    Xu, Zejun
    Yang, Chenguang
    Ma, Hongbin
    Fu, Menyin
    2014 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2014, : 1463 - 1468
  • [8] Integrating Strain Gauge Feedback with Adaptive Sliding Mode Motion Control for Piezoelectric Nanopositioning Stage
    Zeng, Xianfeng
    Nan, Feng
    Li, Tengfei
    Mo, Changchao
    Su, Jiaqiu
    Wei, Kaihong
    Zhang, Xiaozhi
    ACTUATORS, 2025, 14 (02)
  • [9] UDE-Based Adaptive Sliding Mode Control of a Piezoelectric Nanopositioning Stage
    Xu, Qingsong
    2016 AMERICAN CONTROL CONFERENCE (ACC), 2016, : 673 - 678
  • [10] Nonlinear adaptive control based on fuzzy sliding mode technique and fuzzy-based compensator
    Nguyen, Sy Dzung
    Vo, Hoang Duy
    Seo, Tae-Il
    ISA TRANSACTIONS, 2017, 70 : 309 - 321