Nonlinear system modelling: how to estimate the highest significant order

Chiras, Neophytos; Evans, C.; Rees, D.; Solomou, M.

doi:10.1109/imtc.2002.1006866

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…Підвищення вимог до надійності автоматів управління, двигунів та іншого складного промислового обладнання обумовив значний розвиток методів непараметричної ідентифікації таких систем у частотній області. Так, наприклад, випробування дослідного зразка авіаційної турбіни компанії Rolls-Royce та проведений аналіз впливу робочого режиму на швидкість валу дали можливість за допомогою тестових СНС розробити динамічну модель даного двигуна та прогнозувати його поведінку в майбутніх польотах [20]. Зміна робочого режиму (зменшення або збільшення потоку пального) відбувалася за законами мультисинуса, трирівневого сигналу та бінарної послідовності максимальної довжини (псевдовипадкового СНС).…”

Section: основна частинаunclassified

Reasoning Application of Signals With a Regulated Spectr for Control of the Technical State of Radio Waveing Instruments of Water Transportation

Tymoshchuk¹,

Дакі²,

Kolomiets³

2018

НТ

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Section: основна частинаunclassified

Reasoning Application of Signals With a Regulated Spectr for Control of the Technical State of Radio Waveing Instruments of Water Transportation

Tymoshchuk¹,

Дакі²,

Kolomiets³

2018

НТ

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“…When the circuit is not strongly nonlinear, the last two methods are accurate and useful. [8][9][10][11][12] The proposed bu®er is weakly nonlinear and distortion components can be calculated using Volterra series. The Volterra series is a Taylor series, which in the case of a memoryless systems, simpli¯es to a power series, 13-16 also the memory e®ect on the system linearity can be studied.…”

Section: Linearity Analysismentioning

confidence: 99%

Analysis and Design of a Precise Voltage Buffer

Khaneshan

Nematzade

Hadidi

et al. 2015

J CIRCUIT SYST COMP

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An open loop voltage bu®er with an exact unity gain using a positive local feedback technique with a conventional source follower is proposed. Stability of the bu®er is determined by evaluating the location of the poles and zeros and its linearity is studied using Volterra series expansion. The proposed bu®er is laid out in 0.35-m standard CMOS technology. Post layout simulations demonstrate that the bu®er gain is close to unity with less than 0.2% error. The power consumption is 10 mw from a 3.3 V power supply and the achieved total harmonic distortion is À78 dB for a 10 MHz input frequency. Also Monte-Carlo simulations are carried out to investigate e®ects of random mismatches on the circuit operation.

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“…Recently, various NARX (nonlinear autoregressive with exogenous inputs) models have been reported [1] as a mean of describing the input–output relationship of nonlinear systems [2]. The polynomial representation is one of the most common models, and it has shown great potential in the ability of approximating nonlinear input–output relationship and has attracted much attention because it is linear‐in‐parameter [3,4].…”

Section: Introductionmentioning

confidence: 99%

A two‐step scheme for polynomial NARX model identification based on MOEA with prescreening process

Wang

2011

IEEJ Transactions Elec Engng

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Polynomial NARX (nonlinear autoregressive with exogenous) model identification has received considerable attention in last three decades. However, in a high‐order nonlinear system, it is very difficult to obtain the model structure directly even with state‐of‐art algorithms, because the number of candidate monomial terms is huge and increases drastically as the model order increases. Motivated by this fact, in this research, the identification is performed in two steps: firstly a prescreening process is carried out to select a reasonable number of important monomial terms based on two kinds of the importance indices. Then, in the reduced searching space with only the selected important terms, multi‐objective evolutionary algorithm (MOEA) is applied to determine a set of significant terms to be included in the polynomial model with the help of independent validation data. In this way, the whole identification algorithm is implemented efficiently. Numerical simulations are carried out to demonstrate the effectiveness of the proposed identification method. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Nonlinear system modelling: how to estimate the highest significant order

Cited by 5 publications

References 13 publications

Reasoning Application of Signals With a Regulated Spectr for Control of the Technical State of Radio Waveing Instruments of Water Transportation

Reasoning Application of Signals With a Regulated Spectr for Control of the Technical State of Radio Waveing Instruments of Water Transportation

Analysis and Design of a Precise Voltage Buffer

A two‐step scheme for polynomial NARX model identification based on MOEA with prescreening process

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