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.

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

D'Angelo, Massimiliano;
2019-01-01

Abstract

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.
2019
stochastic systems
optimal control
kalman filtering
non-gaussian systems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12606/23731
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