Nonlinear model predictive control based on fuzzy wavelet neural network and chaos optimization

Authors

MEHRNOUSH DAVANIPOUR
HANIEH ASADIPOOYA

DOI

10.3906/elk-1512-176

Abstract

In this paper a combined controller is proposed for nonlinear dynamical systems. The controller is constructed by a fuzzy wavelet network and nonlinear model predictive control. Chaotic optimization, which is fast and robust, is applied to generate optimized controlled input in nonlinear model predictive control. The ability of the fuzzy wavelet neural network and the proposed controller is shown by simulation. It is illustrated that the proposed method is able to increase the speed of tracking in addition to having very little steady state error. Using chaotic optimization makes the controller robust in the presence of noise.

Keywords

Nonlinear model predictive control, fuzzy wavelet neural network, chaos optimization

First Page

3569

Last Page

3577

Recommended Citation

DAVANIPOUR, MEHRNOUSH and ASADIPOOYA, HANIEH (2017) "Nonlinear model predictive control based on fuzzy wavelet neural network and chaos optimization," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 25: No. 5, Article 7. https://doi.org/10.3906/elk-1512-176
Available at: https://journals.tubitak.gov.tr/elektrik/vol25/iss5/7