Abstract—In recent years, intelligent based approaches have been introduced as one of the best potential methods for solving many problems in control literature. Neural Networks (NN) and Fuzzy Logic are widely used in nonlinear system modeling and identification. These approaches require a high number of model parameters, which impose more complex computation. Using Interval Type-2 Fuzzy Neural Network (IT2FNN) method, one needs considerably fewer numbers of required parameters. It can also model uncertainty and nonlinearity of the system much more effectively. In this paper, we suggest to use this neuro – fuzzy based network for nonlinear modeling of a hydraulic actuator. Simulation studies of this challenging benchmark confirm the excellent nonlinear modeling properties of the IT2FNN.
Index Terms—Nonlinear systems, identification, type-2 fuzzy neural network, hydraulic actuator.
Mohsen Vatani, Salman Ahmadi and Saeid Khosravani were with the Department of Electrical Engineering, Amirkabir University of Technology,424 Hafez Ave, Tehran, 15875-4413, Iran (e-mail: m.vatani@aut.ac.ir, ahmadi_salman@aut, ac, ir, khosravani_s@aut.ac.ir).
Cite: Mohsen Vatani, Salman Ahmadi, and Saeid Khosravani, "Hydraulic Actuator Identification Using Interval Type-2Fuzzy Neural Networks," International Journal of Information and Electronics Engineering vol. 2, no. 4, pp. 556-559, 2012.