Two redundant rule based algorithms for time-delay nonlinear models: least squares iterative and particle swarm optimisation
by Yuelin Xu; Yingjiao Rong
International Journal of Modelling, Identification and Control (IJMIC), Vol. 35, No. 3, 2020

Abstract: Two redundant rule based methods are developed for a time-delay nonlinear model in this paper. By using the redundant rule, the time-delay nonlinear model can be turned into a redundant model which contains some redundant terms. Then the least squares iterative and the particle swarm optimisation algorithms are applied to update the parameters and the corresponding time-delay. Compared with the redundant rule based least squares iterative algorithm, the redundant rule based particle swarm optimisation algorithm is more efficient for nonlinear models with complex structures. A simulation example shows that the proposed algorithms are effective.

Online publication date: Tue, 13-Apr-2021

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