Feedback polynomial filtering and control of non-Gaussian linear time-varying systems

被引:17
作者
Cacace, Filippo [1 ]
Conte, Francesco [2 ]
d'Angelo, Massimiliano [3 ]
Germani, Alfredo [4 ]
机构
[1] Univ Campus Biomed Roma, Rome, Italy
[2] Univ Genoa, DITEN, Genoa, Italy
[3] Sapienza Univ Roma, DIAG, Rome, Italy
[4] Univ Aquila, DISIM, Laquila, Italy
关键词
Stochastic systems; Optimal control; Kalman filtering; Non-Gaussian systems;
D O I
10.1016/j.sysconle.2018.11.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper deals with the optimal filtering and optimal output-feedback control of discrete-time, linear time-varying non-Gaussian systems. In the hypothesis that the time-varying and non-Gaussian distributions of the state and measurement noises have bounded and known moments up to a given order, this work extends previous results about polynomial filtering and optimal control to the time-varying case. The properties of the resulting filtering and control algorithms are discussed in the light of a stable recursive representation of the Kronecker powers of the system obtained through a suitable rewriting of the system with an output injection term. The resulting sub-optimal algorithm inherits the structure and the properties of the classical LQG approach but with enhanced performance. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:108 / 115
页数:8
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