Abstract
This paper considers the parameter identification of Wiener systems with colored noise. The difficulty in the identification is that the model is nonlinear and the intermediate variable cannot be measured. Particle swarm optimization is an artificial intelligence evolutionary method and is effective in solving nonlinear optimization problem. In this paper, we obtain the identification model of the Wiener system and then transfer the parameter identification problem into an optimization problem. Then, we derive a particle swarm optimization iterative (PSOI) identification algorithm to identify the unknown parameter of the Wiener system. Furthermore, a gradient iterative identification algorithm is proposed to compare with the particle swarm optimization iterative algorithm. Numerical simulation is carried out to evaluate the performance of the PSOI algorithm and the gradient iterative algorithm. The simulation results indicate that the proposed algorithms are effective and the PSOI algorithm can achieve better performance over the gradient iterative algorithm.
Highlights
Almost all practical systems are nonlinear [1,2,3]
This paper considers the parameter identification of Wiener systems with colored noise
The Wiener nonlinear system consists of a dynamic linear subsystem and a static nonlinear subsystem and has the characteristics of complex structure between subsystems [12, 13]
Summary
Almost all practical systems are nonlinear [1,2,3]. Many identification methods have been developed for linear systems [4, 5], bilinear systems [6,7,8], and nonlinear systems [9]. The basic idea of particle swarm optimization algorithm is to find the optimal solution through collaboration and information sharing among individuals in the group [25]. This algorithm has attracted the attention of academia with the advantages of easy implementation, high precision, and fast convergence [26]. We use the particle swarm optimization algorithm and the gradient iterative algorithm to identify the unknown parameters of the Wiener systems with colored noise.
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