Linear discrete-time state space realization of a modified quadruple tank system with state estimation using Kalman filter

Sazuan Nazrah Mohd. Azam

doi:10.1088/1742-6596/783/1/012013

Linear discrete-time state space realization of a modified quadruple tank system with state estimation using Kalman filter

Sazuan Nazrah Mohd. Azam

Research output: Contribution to journal › Conference article › Research › peer-review

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Abstract

In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing dynamics of the system of stochastic differential equations is linearized to produce the deterministic-stochastic linear transfer function. Then the linear transfer function is discretized to produce a linear discrete-time state space model that has a deterministic and a stochastic component. The filtered part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations.

Original language	English
Article number	012013
Book series	Journal of Physics: Conference Series
Volume	783
Number of pages	11
ISSN	1742-6596
DOIs	https://doi.org/10.1088/1742-6596/783/1/012013
Publication status	Published - 2017
Event	13th European Workshop on Advanced Control and Diagnosis - Graduate School of Engineering "Hautes Etudes d'Ingenieur", Lille, France Duration: 17 Nov 2016 → 19 Nov 2016 http://acd2016.eu/

Workshop

Workshop	13th European Workshop on Advanced Control and Diagnosis
Location	Graduate School of Engineering "Hautes Etudes d'Ingenieur"
Country/Territory	France
City	Lille
Period	17/11/2016 → 19/11/2016
Internet address	http://acd2016.eu/

Bibliographical note

Content from this work may be used under the terms of theCreative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd

Keywords

Filtering methods in signal processing
Mathematical analysis
Other topics in statistics
Multivariable control systems
Discrete control systems
Linear control systems
Simulation, modelling and identification
Signal processing theory
Control system analysis and synthesis methods

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10.1088/1742-6596/783/1/012013

Azam 2017 JFinal published version, 689 KB

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title = "Linear discrete-time state space realization of a modified quadruple tank system with state estimation using Kalman filter",

abstract = "In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing dynamics of the system of stochastic differential equations is linearized to produce the deterministic-stochastic linear transfer function. Then the linear transfer function is discretized to produce a linear discrete-time state space model that has a deterministic and a stochastic component. The filtered part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations.",

keywords = "Filtering methods in signal processing, Mathematical analysis, Other topics in statistics, Multivariable control systems, Discrete control systems, Linear control systems, Simulation, modelling and identification, Signal processing theory, Control system analysis and synthesis methods",

author = "{Mohd. Azam}, {Sazuan Nazrah}",

note = "Content from this work may be used under the terms of theCreative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd; 13th European Workshop on Advanced Control and Diagnosis, ACD2016 ; Conference date: 17-11-2016 Through 19-11-2016",

year = "2017",

doi = "10.1088/1742-6596/783/1/012013",

language = "English",

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AU - Mohd. Azam, Sazuan Nazrah

N1 - Content from this work may be used under the terms of theCreative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd

PY - 2017

Y1 - 2017

N2 - In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing dynamics of the system of stochastic differential equations is linearized to produce the deterministic-stochastic linear transfer function. Then the linear transfer function is discretized to produce a linear discrete-time state space model that has a deterministic and a stochastic component. The filtered part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations.

AB - In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing dynamics of the system of stochastic differential equations is linearized to produce the deterministic-stochastic linear transfer function. Then the linear transfer function is discretized to produce a linear discrete-time state space model that has a deterministic and a stochastic component. The filtered part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations.

KW - Filtering methods in signal processing

KW - Mathematical analysis

KW - Other topics in statistics

KW - Multivariable control systems

KW - Discrete control systems

KW - Linear control systems

KW - Simulation, modelling and identification

KW - Signal processing theory

KW - Control system analysis and synthesis methods

U2 - 10.1088/1742-6596/783/1/012013

DO - 10.1088/1742-6596/783/1/012013

M3 - Conference article

VL - 783

JO - Journal of Physics: Conference Series (Online)

JF - Journal of Physics: Conference Series (Online)

SN - 1742-6596

M1 - 012013

T2 - 13th European Workshop on Advanced Control and Diagnosis

Y2 - 17 November 2016 through 19 November 2016

ER -

Linear discrete-time state space realization of a modified quadruple tank system with state estimation using Kalman filter

Abstract

Workshop

Bibliographical note

Keywords

Access to Document

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Cite this