Fractional Wiener System Identification Using Heuristic Optimization Technique Based on Key Term Principle

Lamia Sersour1, Tounsia Djamah2, Maamar Bettayeb3

  • 1University of Mouloud Mammeri, Tizi Ouzou, Algeria
  • 2University Mouloud Mammeri of Tizi-Ouzou,Tizi-ouzou,ALGERIA
  • 3Univ of Sharjah



Invited Session


11:00 - 12:28 | Wed 28 Aug | 019 | WeAT10

Fractional Order Systems and Controllers for Industrial Processes: Advances and Prospects

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In this work, identification of fractional Wiener system is considered; this nonlinear class is defined by the separation of the nonlinear static behavior and the linear invariant time behavior into different blocks. For this purpose, the parameters of the linear and the nonlinear part of the Wiener system as well as the fractional order are estimated, using the heuristic particle swarm optimization (PSO). It is combined with the key term principle to determine the unmeasurable internal variable. In order to confirm the performance of this approach, a simulation example is considered for different signal to noise ratios.

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