Novel approach identifies nonlinear functions in Wiener systems, suggesting effective optimization solutions.
A novel identification approach is proposed for Wiener systems to avoid error accumulation. The proposed approach identifies the linear and nonlinear part respectively. Firstly, a sequence of step signals with various amplitudes is supplied to the system. The structure of the static nonlinear function is obtained from the input step signals and their corresponding steady-state responses. A novel Artificial Bee Colony (NABC) algorithm is developed to solve the optimization problems and the two experiment studies show that the proposed identification procedure is effective.
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Liye Liu (2026) studied this question.
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