Distribution Steering for Discrete-Time Uncertain Ensemble Systems

成果类型:
Article
署名作者:
Wu, Guangyu; Tsiotras, Panagiotis; Lindquist, Anders
署名单位:
Shanghai Jiao Tong University; University System of Georgia; Georgia Institute of Technology; University System of Georgia; Georgia Institute of Technology; Anhui University
刊物名称:
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
ISSN/ISSBN:
0018-9286
DOI:
10.1109/TAC.2026.3657277
发表日期:
2026
关键词:
Covariance assignment
摘要:
Ensemble systems appear frequently in many engineering applications and, as a result, they have become an important research topic in control theory. These systems are best characterized by the evolution of their underlying state distribution. Despite the work to date, few results exist dealing with the problem of directly modifying (i.e., steering) the distribution of an ensemble system. In addition, in most existing results, the distribution of the states of an ensemble of discrete-time systems is assumed to be Gaussian. However, in case the system parameters are uncertain, it is not always realistic to assume that the distribution of the system follows a Gaussian distribution, thus complicating the solution of the overall problem. In this article, we address the general distribution steering problem for first-order discrete-time ensemble systems, where the distributions of the system parameters and the states are arbitrary with finite first few moments. Linear system dynamics are considered using the method of power moments to transform the original infinite-dimensional problem into a finite-dimensional one. We also propose a control law for the ensuing moment system, which allows us to obtain the power moments of the desired control inputs. Finally, we solve the inverse problem to obtain the feasible control inputs from their corresponding power moments. We provide a numerical example to validate our theoretical developments.