首页|基于滤波器的浸入与不变自适应控制

基于滤波器的浸入与不变自适应控制

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针对机电伺服系统存在参数不确定、未建模动态及时变扰动这一问题,提出一种基于滤波器的浸入与不变自适应算法,该算法能够准确估计伺服系统中的未知参数.首先,构造系统状态及回归函数的滤波器,再根据滤波后的辅助变量构造参数估计器;然后,依据浸入与不变理论设计参数估计器中的辅助函数,从而保证参数估计误差的收敛性.此外,为了进一步降低集总扰动对系统闭环性能的影响,提出一种扰动观测器,这种扰动观测器结构简单,并且能保证估计误差的渐近稳定,从而有效地补偿系统中的未建模动态和外部扰动.最后,利用Lyapunov理论分别证明了参数估计器、扰动观测器及闭环系统的稳定性,仿真与实验结果验证了所提出的自适应方法及扰动观测器的有效性.
Filter-based immersion and invariance adaptive control
This paper proposes a filter-based immersion and invariance adaptive controller for mechatronics servo systems with parameter uncertainties,unmodeled dynamics and time-varying disturbance.First,a filter of the system states and regression function is constructed,and a parameter estimator is built based on the filtered auxiliary variables.Next,the auxiliary function in the parameter estimator needs to be designed according to the immersion and invariance theory to ensure the convergence of the parameter estimation error.Moreover,this paper proposes a disturbance observer to further reduce the impact of lumped disturbances on the closed-loop performance of the system.This disturbance observer,which is simple in structure,can ensure the asymptotic stability of the estimation error.The Lyapunov theory is used to prove the stability of the parameter estimator,the disturbance observer,and the closed-loop system,respectively,thus can efficiently compensate for unmodelled dynamics and external disturbances in the system.The simulation and experimental results demonstrate the effectiveness of the proposed adaptive method and the disturbance observer.

immersion and invariancedisturbance observermechatronic servo systemadaptive controlstates filtersasymptotic stability

陈伟、胡健、姚建勇、聂伟荣、周海波

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南京理工大学机械工程学院,南京 210094

中南大学高性能复杂制造国家重点实验室,长沙 410000

浸入与不变 扰动观测器 机电伺服系统 自适应控制 状态滤波器 渐近稳定

国家自然科学基金面上项目航天伺服驱动与传动技术实验室开放基金项目中央高校基本科研业务费专项资金项目

51975294LASAT-2021-050330922010706

2024

控制与决策
东北大学

控制与决策

CSTPCD北大核心
影响因子:1.227
ISSN:1001-0920
年,卷(期):2024.39(1)
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