Title :
The Research of Nonlinear Control Based on Fuzzy Neural Network
Author :
Fan Yuan-yuan ; Sang Ying-jun
Author_Institution :
Fac. of Math. & Phys., Huaiyin Inst. of Technol., Huaian, China
Abstract :
This paper discussed and researched the structure and algorithm of fuzzy neural network controller based on the character of fuzzy logic and neural network theory. For the nonlinear system characteristics of uncertainty, high order and hysteresis, this paper used the fuzzy neural network technology to control nonlinear system and improved the control quality obviously. Take the single inverted pendulum for example, the paper constructed the nonlinear mathematic model, realized the control with the method of the adaptive fuzzy neural network, and compared with control method of liner quadratic regulator, the simulation results indicate that the method of adaptive fuzzy neural network can realize the stabilization of control better without the linear model of system, and has a higher robustness.
Keywords :
adaptive control; fuzzy control; fuzzy logic; linear quadratic control; neurocontrollers; nonlinear control systems; pendulums; robust control; adaptive fuzzy neural network; control quality; fuzzy logic; fuzzy neural network controller; fuzzy neural network technology; linear quadratic regulator; neural network theory; nonlinear control system; nonlinear mathematic model; nonlinear system characteristics; robustness; single inverted pendulum; stabilization; Adaptation model; Adaptive systems; Artificial neural networks; Control systems; Data models; Fuzzy control; Fuzzy neural networks; ANFIS; LQR control; nonlinear; robustness; stabilization;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
DOI :
10.1109/iCECE.2010.597