Design of Fuzzy Neural Network Based Multi-Variables Controller for Manipulators
Keywords:
fuzzy neural network, multivariable control, decoupling, manipulator controlAbstract
This paper proposes a robust multivariable control design by intelligent control that uses a fuzzy neural network by producing robustness capable of automatically controlling gain against a conventional, fixed PID control system. This structural feature of the proposed controller forms a nonlinear deviation compensator using fuzzy neural networks. Therefore, in multidimensionality the inverse dynamic model portion of the control law is referred to as a linearizing and decoupling control law. This method uses a control law where parameter response leads to critical damping and adaptive changes in gain according to time, making it possible to decouple mutual interference in each multivariable system.Published
2009-07-05
How to Cite
Sato, Y. (2009). Design of Fuzzy Neural Network Based Multi-Variables Controller for Manipulators. Proceedings of the 53rd Annual Meeting of the ISSS - 2009, Brisbane, Australia, 1(1). Retrieved from https://journals.isss.org/index.php/proceedings53rd/article/view/1201
Issue
Section
Systems Modeling and Simulation