Title: Two redundant rule based algorithms for time-delay nonlinear models: least squares iterative and particle swarm optimisation
Authors: Yuelin Xu; Yingjiao Rong
Addresses: The Science and Technology on Near-Surface Detection Laboratory, Wuxi, 214028, China ' The Science and Technology on Near-Surface Detection Laboratory, Wuxi, 214028, China
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.
Keywords: nonlinear model; particle swarm optimisation algorithm; time-delay; parameter estimation; redundant rule; least squares iterative.
International Journal of Modelling, Identification and Control, 2020 Vol.35 No.3, pp.258 - 264
Received: 11 May 2020
Accepted: 20 Jun 2020
Published online: 13 Apr 2021 *