基于非均匀采样系统的无模型自适应控制  

Model-Free Adaptive Control Based on Non-uniform Sampling System

作　　者：叶金鑫 谢丽蓉[1] 王宏伟[2] YE Jinxin;XIE Lirong;WANG Hongwei(Xinjiang University,Urumqi 830000,China;Dalian University of Technology,Dalian 116000,China)

机构地区：[1]新疆大学,乌鲁木齐830000 [2]大连理工大学,辽宁大连116000

出　　处：《电光与控制》2022年第5期48-54,共7页Electronics Optics & Control

基　　金：国家自然科学基金(61863034)。

摘　　要：针对输入非均匀刷新和输出周期性采样的非线性系统难以控制的问题,采用数据驱动策略,提出一种新的无模型自适应控制方法。首先,使用跟踪-微分器对系统输出数据进行滤波,进而利用该输入输出数据在等价动态平衡点处建立动态化模型,设计了无模型自适应控制器;其次,利用最速下降法对控制律和伪雅可比矩阵(PJM)估计中的惩罚系数进行迭代优化,并对该控制方法稳定性进行分析,该控制方法的优点是减少扰动误差的影响,提高了参数优化能力;最后,通过仿真非均匀采样离散时间非线性系统的实例验证了所提方法的有效性。A new model-free adaptive control algorithm is proposed by using a data-driven strategy to address the problem that it is difficult to control a nonlinear system with non-uniformly refreshed input and periodically sampled output.Firstly,the system output data is filtered by using a tracking-differentiator,and then the dynamic model is established at the equivalent dynamic equilibrium point by using this input-output data,and a model-free adaptive controller is designed.Secondly the penalty coefficients in the control law and Pseudo Jacobian Matrix(PJM)estimation are iteratively optimized by using the most rapid descent method,and the stability of the algorithm is analyzed.The advantages of it are: Reducing the influence of disturbance error and improving the ability of parameter optimization.Finally,the effectiveness of the proposed method is verified by an example of simulating a discrete-time nonlinear system with non-uniform sampling.

关 键 词：非均匀采样系统 自适应控制 建模 数据驱动 伪雅可比矩阵(PJM) 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]