Designing flexible neuro-fuzzy system based on sliding mode controller for magnetic levitation systems

作     者：Mohammadi, Zahra Teshnehlab, Mohammad Shoorehdeli, Mahdi Aliyari 

作者机构：Electrical Engineering Department Science and Research Branch of Islamic Azad University Tehran Iran Faculty of Electrical Engineering Department of Control Engineering K. N. Toosi University of Technology Tehran Iran Faculty of Electrical Engineering Department of Mechatronics Engineering K. N. Toosi University of Technology Tehran Iran 

出 版 物：《International Journal of Computer Science Issues》 (Int. J. Comput. Sci. Issues)

年 卷 期：2011年第8卷第4 4-1期

页      面：160-171页

核心收录：

主　　题：Controllers 

摘      要：This study presents a novel controller of magnetic levitation system by using new neuro-fuzzy structures which called flexible neuro-fuzzy systems. In this type of controller we use sliding mode control with neuro-fuzzy to eliminate the Jacobian of plant. At first, we control magnetic levitation system with Mamdanitype neuro-fuzzy systems and logical-type neuro-fuzzy systems separately and then we use two types of flexible neuro-fuzzy systems as controllers. Basic flexible OR-type neuro-fuzzy inference system and basic compromise AND-type neuro-fuzzy inference system are two new flexible neuro-fuzzy controllers which structure of fuzzy inference system (Mamdani or logical) is determined in the learning process. We can investigate with these two types of controllers which of the Mamdani or logical type systems has better performance for control of this plant. Finally we compare performance of these controllers with sliding mode controller and RBF sliding mode controller.