Neuro-Fuzzy Control for Generalised Nonlinear Systems under a Recursive Framework

Authors

Abstract

This paper proposes a general recursive state- space Neuro-Fuzzy control framework. It combines a eight- layered neuro-fuzzy architecture with a state feedback quadratic stabilising controller. Both the model and controller are updated online within a constrained unscented Kalman filter. Results from a benchmark Multi-Input and Multi-Output system demonstrate the effectiveness of the proposed approach.

Keywords

Noise measurement, Neurons, Two dimensional displays, Electrical engineering, Information technology, Linear matrix inequalities, Nonlinear systems

Subject

Neuro-Fuzzy control

Conference

ICITEE2018 - 10th International Conference on Information Technology and Electrical Engineering, July 2018

DOI