受控自回归系统的带惩罚项梯度辨识算法  

Gradient identification algorithms based on the penalty criterion function for controlled autoregressive systems

作　　者：孙焕琪 熊伟丽[1] 丁锋[1] SUN Huan-qi;XIONG Wei-li;DING Feng(School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China)

机构地区：[1]江南大学物联网工程学院,江苏无锡214122

出　　处：《控制与决策》2024年第8期2719-2727,共9页Control and Decision

基　　金：国家自然科学基金项目(62273167).

摘　　要：基于带惩罚项准则函数,研究受控自回归系统的辨识问题.首先,通过负梯度搜索,极小化带惩罚项的准则函数,得到计算参数估计的递推关系,并利用一维线搜索确定最佳步长,推导带惩罚项投影梯度辨识算法和带惩罚项随机梯度辨识算法;然后,为了提高带惩罚项随机梯度算法的收敛速度,使用多新息辨识理论,推导带惩罚项多新息随机梯度辨识算法;最后,通过仿真实例验证所提出算法的有效性.Based on the criterion function with penalty,the identification problem of controlled autoregressive systems is studied.Through the gradient search,the recursive relationship of parameter estimation is obtained by minimizing the criterion function with penalty,and the optimal step-size is deducted to obtain the parameter estimation through the one-dimensional line search.The projection identification algorithm with penalty and the stochastic gradient identification algorithm with penalty are proposed.By using the multi-innovation theory,a multi-innovation stochastic gradient identification algorithm with penalty is proposed.The effectiveness of the proposed algorithm is verified by the simulation.

关 键 词：参数估计 随机梯度 多新息辨识 惩罚项 准则函数 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]