Reduction of data amount in data-driven design of linear quadratic regulators  

作　　者：Shinsaku Izumi Xin Xin 

机构地区：[1]School of Systems Engineering,Kochi University of Technology,Kami,Kochi,782-8502,Japan [2]School of Automation,Southeast University,and Key Laboratory of Measurement and Control of Complex Systems of Engineering,Ministry of Education,Nanjing,210096,Jiangsu,China

出　　处：《Control Theory and Technology》2024年第4期532-542,共11页控制理论与技术（英文版）

摘　　要：This paper discusses the data-driven design of linear quadratic regulators,i.e.,to obtain the regulators directly from experimental data without using the models of plants.In particular,we aim to improve an existing design method by reducing the amount of the required experimental data.Reducing the data amount leads to the cost reduction of experiments and computation for the data-driven design.We present a simplified version of the existing method,where parameters yielding the gain of the regulator are estimated from only part of the data required in the existing method.We then show that the data amount required in the presented method is less than half of that in the existing method under certain conditions.In addition,assuming the presence of measurement noise,we analyze the relations between the expectations and variances of the estimated parameters and the noise.As a result,it is shown that using a larger amount of the experimental data might mitigate the effects of the noise on the estimated parameters.These results are verified by numerical examples.

关 键 词：Data-driven design Linear quadratic regulators Linear systems Riccati equation Stochastic properties 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]