Identification of Continuous-Time Systems with Time Delays by Global Optimization Algorithms and Ant Colony Optimization

Papliński, Janusz P.

doi:10.5772/6102

Cited by 4 publications

(1 citation statement)

References 12 publications

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“…However, it can be noticed that the performance of this algorithm is reduced if the noise and number of parameters to be identified are increasing. In (Janusz, 2008), the author considers the parameter estimation problem of MISO CT systems with multiple time delays via an ant colony optimization algorithm. However, this algorithm is not robust to high levels of noise.…”

Section: Introductionmentioning

confidence: 99%

Identification of continuous-time hybrid “Box–Jenkins” systems with multiple unknown time delays using two-stage parameter estimation algorithm

Ghoul

2019

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Purpose This study/paper aims to present a separable identification algorithm for a multiple input single output (MISO) continuous time (CT) hybrid “Box–Jenkins”. Design/methodology/approach This paper proposes an optimal method for the identification of MISO CT hybrid “Box–Jenkins” systems with unknown time delays by using the two-stage recursive least-square (TS-RLS) identification algorithm. Findings The effectiveness of the proposed scheme is shown with application to a simulation example. Originality/value A two-stage recursive least-square identification method is developed for multiple input single output continuous time hybrid “Box–Jenkins” system with multiple unknown time delays from sampled data. The proposed technique allows the division of the global CT hybrid “Box–Jenkins” system into two fictitious subsystems: the first one contains the parameters of the system model, including the multiple unknown time delays, and the second contains the parameters of the noise model. Then the TS-RLS identification algorithm can be applied easily to estimate all the parameters of the studied system.

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Section: Introductionmentioning

confidence: 99%

Identification of continuous-time hybrid “Box–Jenkins” systems with multiple unknown time delays using two-stage parameter estimation algorithm

Ghoul

2019

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Identification of Continuous-Time Systems with Multiple Unknown Time Delays Using an Output Error Method from Sampled Data

Ghoul

Taarit

Ksouri

2017

Circuits Syst Signal Process

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Prediction Error Identification Method for Continuous-time Systems Having Multiple Unknown Time Delays

Ghoul

2020

Int. J. Control Autom. Syst.

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Identification of Continuous-Time Systems with Time Delays by Global Optimization Algorithms and Ant Colony Optimization

Cited by 4 publications

References 12 publications

Identification of continuous-time hybrid “Box–Jenkins” systems with multiple unknown time delays using two-stage parameter estimation algorithm

Identification of continuous-time hybrid “Box–Jenkins” systems with multiple unknown time delays using two-stage parameter estimation algorithm

Identification of Continuous-Time Systems with Multiple Unknown Time Delays Using an Output Error Method from Sampled Data

Prediction Error Identification Method for Continuous-time Systems Having Multiple Unknown Time Delays

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