A novel backstepping adaptive control approach based on fuzzy neural network disturbance observer

2010 ◽  
Author(s):  
Li Zhou ◽  
Shumin Fei ◽  
Jinxing Lin
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Disturbance Observer ◽  
Fuzzy Neural Network ◽  
Control Approach ◽  
Fuzzy Neural

scholarly journals Multiple Loop Fuzzy Neural Network Fractional Order Sliding Mode Control of Micro Gyroscope

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2124
Author(s):  
Yunmei Fang ◽  
Fang Chen ◽  
Juntao Fei
Keyword(s):  
Neural Network ◽  
Fractional Order ◽  
Fuzzy Neural Network ◽  
Sliding Mode ◽  
Parameter Uncertainties ◽  
Control Approach ◽  
Switching Law ◽  
Lumped Parameter ◽  
Fuzzy Neural ◽  
The Stability

In this paper, an adaptive double feedback fuzzy neural fractional order sliding control approach is presented to solve the problem that lumped parameter uncertainties cannot be measured and the parameters are unknown in a micro gyroscope system. Firstly, a fractional order sliding surface is designed, and the fractional order terms can provide additional freedom and improve the control accuracy. Then, the upper bound of lumped nonlinearities is estimated online using a double feedback fuzzy neural network. Accordingly, the gain of switching law is replaced by the estimated value. Meanwhile, the parameters of the double feedback fuzzy network, including base widths, centers, output layer weights, inner gains, and outer gains, can be adjusted in real time in order to improve the stability and identification efficiency. Finally, the simulation results display the performance of the proposed approach in terms of convergence speed and track speed.

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