摘要
递推最小二乘(Recursive Least Squares,RLS)算法因其简单、快速的特点,在微振动自适应控制领域被广泛应用。由于微振动主动控制系统中扰动环境的特殊性及复杂性,需要重点考虑微振动控制中所采用的参数自适应算法在参数估计过程中的鲁棒性。针对多输入多输出(Multiple Input Multiple Output,MIMO)微振动主动控制系统,基于无限冲激响应(Infinite Impulse Response,IIR)滤波器,提出一种结合死区和归一化的MIMO鲁棒参数自适应算法,并给出其详细的算法推导与收敛性分析。在此基础上,通过构建三自由度微振动主动振动控制实验系统,针对单频窄带扰动、双频窄带扰动展开了对比实验分析,相关的实验结果验证了所提出鲁棒参数自适应算法的可行性和鲁棒性。
Recursive Least Squares algorithm is widely adopted in the field of micro-vibration adaptive control because of its sim⁃plicity and speed.Due to the particularity and complexity of the disturbance environment in the micro-vibration active control appli⁃cation,the robustness of the parameter adaptive algorithm used in the micro-vibration control needs to be considered.For the Multi⁃ple-Input Multiple-Output(MIMO)active vibration control system,this paper presents a MIMO robust parameter adaptive algo⁃rithm based on an Infinite Impulse Response(IIR)filter.This robust parameter adaptive algorithm takes advantage of the dead zone and normalization.The deducing process and convergence analysis of the robust parameter adaptive algorithm are illustrated in detail.A 3-DOF real time micro-vibration control experimental platform has been constructed.Comparison are provided with sine disturbance,double sine disturbance and broadband disturbance.Experimental results confirm the feasibility and robust of the pro⁃posed algorithm.
作者
方昱斌
朱晓锦
高志远
杨龙飞
张小兵
FANG Yu‑bin;ZHU Xiao‑jin;GAO Zhi‑yuan;YANG Long‑fei;ZHANG Xiao‑bing(School of Intelligent Manufacturing,Nanjing University of Science and Technology,Nanjing 210094,China;School of Mechatronic Engineering and Automation,Shanghai University,Shanghai 200444,China;School of Energy and Power Engineering,Nanjing University of Science and Technology,Nanjing 210094,China)
出处
《振动工程学报》
EI
CSCD
北大核心
2024年第2期237-246,共10页
Journal of Vibration Engineering
基金
中国博士后科学基金资助项目(2021M691598)
国家自然科学基金面上项目(52175101)。
关键词
微振动主动控制
参数自适应算法
多输入多输出
RLS
鲁棒自适应
micro⁃vibration active control
parameter adaptive algorithm
multiple input multiple output
RLS
robust adaptive
