Design of Fuzzy Neural Network Based Multi-Variables Controller for Manipulators
Keywords:fuzzy neural network, multivariable control, decoupling, manipulator control
AbstractThis 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.
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
Systems Modeling and Simulation