ARMAX models are widely used in identification and are a standard tool in control engineering for both system description and control design. These models, however, can be non realistic in many practical contexts because of the presence of measurement errors that play an important role in applications like fault diagnosis and optimal filtering. ARMAX models can be enhanced by introducing also additive error terms on the input and output observations. This scheme, that can be denoted as “ARMAX + noise”, belongs to the errors–in–variables family and allows taking into account the presence of both process disturbances and measurement noise. This paper proposes a three–step procedure for identifying “ARMAX + noise” processes. The first step of the identification algorithm in based on an iterative search procedure while the second and third ones rely on simple least–squares formulas. The paper reports also the results of some Monte Carlo simulations that underline the effectiveness of the proposed approach.

Identification of ARMAX models with noisy input and output / R. Diversi; R. Guidorzi; U. Soverini. - ELETTRONICO. - (2011), pp. 13121-13126. (Intervento presentato al convegno 18th IFAC World Congress tenutosi a Milano nel 28 Agosto - 2 Settembre, 2011) [10.3182/20110828-6-IT-1002.00469].

Identification of ARMAX models with noisy input and output

DIVERSI, ROBERTO;GUIDORZI, ROBERTO;SOVERINI, UMBERTO
2011

Abstract

ARMAX models are widely used in identification and are a standard tool in control engineering for both system description and control design. These models, however, can be non realistic in many practical contexts because of the presence of measurement errors that play an important role in applications like fault diagnosis and optimal filtering. ARMAX models can be enhanced by introducing also additive error terms on the input and output observations. This scheme, that can be denoted as “ARMAX + noise”, belongs to the errors–in–variables family and allows taking into account the presence of both process disturbances and measurement noise. This paper proposes a three–step procedure for identifying “ARMAX + noise” processes. The first step of the identification algorithm in based on an iterative search procedure while the second and third ones rely on simple least–squares formulas. The paper reports also the results of some Monte Carlo simulations that underline the effectiveness of the proposed approach.
2011
Proceedings of the 18th IFAC World Congress
13121
13126
Identification of ARMAX models with noisy input and output / R. Diversi; R. Guidorzi; U. Soverini. - ELETTRONICO. - (2011), pp. 13121-13126. (Intervento presentato al convegno 18th IFAC World Congress tenutosi a Milano nel 28 Agosto - 2 Settembre, 2011) [10.3182/20110828-6-IT-1002.00469].
R. Diversi; R. Guidorzi; U. Soverini
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/107181
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