Hydraulic Actuator Identification Using Inertval Type-2 Fuzzy Neural Networks
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 (IT2FNX) 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 1T2FNN.
Nonlinear Systems Identification Type-2 Fuzzy Neural Network Hydraulic Actuator
Mohsen Vatani Salman Ahmadi Saeid Khosravani
Department of Electrical Engineering Amirkabir University of Technology Tehran, Iran
国际会议
重庆
英文
287-291
2011-01-21（万方平台首次上网日期，不代表论文的发表时间）