Discrete-time inverse linear quadratic optimal control over fnite time-horizon under noisy output measurements  被引量:1

在线阅读下载全文

作  者:Han Zhang Yibei Li Xiaoming Hu 

机构地区:[1]Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China [2]Key Laboratory of System Control and Information Processing,Ministry of Education of China,Shanghai 200240,China [3]Shanghai Engineering Research Center of Intelligent Control and Management,Shanghai 200240,China [4]Department of Mathematics,KTH Royal Institute of Technology,10044 Stockholm,Sweden

出  处:《Control Theory and Technology》2021年第4期563-572,共10页控制理论与技术(英文版)

摘  要:In this paper,the problem of inverse quadratic optimal control over fnite time-horizon for discrete-time linear systems is considered.Our goal is to recover the corresponding quadratic objective function using noisy observations.First,the identifability of the model structure for the inverse optimal control problem is analyzed under relative degree assumption and we show the model structure is strictly globally identifable.Next,we study the inverse optimal control problem whose initial state distribution and the observation noise distribution are unknown,yet the exact observations on the initial states are available.We formulate the problem as a risk minimization problem and approximate the problem using empirical average.It is further shown that the solution to the approximated problem is statistically consistent under the assumption of relative degrees.We then study the case where the exact observations on the initial states are not available,yet the observation noises are known to be white Gaussian distributed and the distribution of the initial state is also Gaussian(with unknown mean and covariance).EM-algorithm is used to estimate the parameters in the objective function.The efectiveness of our results are demonstrated by numerical examples.

关 键 词:Inverse optimal control Linear quadratic regulator Statistical consistency EM-ALGORITHM 

分 类 号:O17[理学—数学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象