UFIR Filter for Networked Systems with Multiplicative Process Noises, Uncertain Stochastic Parameters and One-Step Random Delays Observations (I)

Resumen: The problem of network systems with stochastic uncertain failures at the transmitted measurements and undetermined knowledge of the system parameters is addressed with the UFIR filter. The measurement output is multiple transmitted which random one-step packet delay and described by Bernoulli process according to the probability detected of this phenomena. the multiplicative noise is detected in the model and the observation, which are described by random variables. Linear filters such as the Kalman filter, the game theory $H_{infty }$, and the UFIR filter are developed based on the transformed model, which not depend on delays in the sense to obtain a minimum variance despite the errors at the system and achieve comparison the effectiveness and robustness obtained in real situations. A simulation example using the GPS coordinates of a vehicle illustrates the effectiveness o the proposed methodology.

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Karen Uribe-Murcia & Yuriy S. Shmaliy. UFIR Filter for Networked Systems with Multiplicative Process Noises, Uncertain Stochastic Parameters and One-Step Random Delays Observations (I). Memorias del Congreso Nacional de Control Automático, pp. 364-369, 2021.

Palabras clave

Delayed data, missing data, unbiased FIR filter

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