scholarly journals Adaptive Backstepping Fuzzy Neural Network Fractional-Order Control of Microgyroscope Using a Nonsingular Terminal Sliding Mode Controller

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Juntao Fei ◽  
Xiao Liang
Keyword(s):  
Neural Network ◽  
Fractional Order ◽  
Fuzzy Neural Network ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Terminal Sliding Mode ◽  
Nonsingular Terminal Sliding Mode ◽  
Control Scheme ◽  
Fuzzy Neural ◽  
Neural Network Compensator

An adaptive fractional-order nonsingular terminal sliding mode controller for a microgyroscope is presented with uncertainties and external disturbances using a fuzzy neural network compensator based on a backstepping technique. First, the dynamic of the microgyroscope is transformed into an analogical cascade system to guarantee the application of a backstepping design. Then, a fractional-order nonsingular terminal sliding mode surface is designed which provides an additional degree of freedom, higher precision, and finite convergence without a singularity problem. The proposed control scheme requires no prior knowledge of the unknown dynamics of the microgyroscope system since the fuzzy neural network is utilized to approximate the upper bound of the lumped uncertainties and adaptive algorithms are derived to allow online adjustment of the unknown system parameters. The chattering phenomenon can be reduced simultaneously by the fuzzy neural network compensator. The stability and finite time convergence of the system can be established by the Lyapunov stability theorem. Finally, simulation results verify the effectiveness of the proposed controller and the comparison of root mean square error between different fractional orders and integer order is given to signify the high precision tracking performance of the proposed control scheme.

scholarly journals Novel Fuzzy Neural Nonsingular Terminal Sliding Mode Control of MEMS Gyroscope

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Zhe Wang ◽  
Juntao Fei
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Sliding Mode ◽  
Double Loop ◽  
Model Uncertainties ◽  
External Disturbances ◽  
Terminal Sliding Mode ◽  
Nonsingular Terminal Sliding Mode ◽  
Fuzzy Neural ◽  
Recurrent Fuzzy Neural Network

This paper attempts to improve the robustness and rapidity of a microgyroscope sensor by presenting a double-loop recurrent fuzzy neural network based on a nonsingular terminal sliding mode controller. Compared with the traditional control method, the proposed strategy can obtain faster dynamic response speed and lower steady-state error with high robustness in the presence of system uncertainties and external disturbances. A nonlinear terminal sliding mode controller is designed to guarantee finite-time high-precision convergence of the sliding surface and meanwhile to eliminate the effect of singularity. Moreover, an exponential approach law is used to accelerate the convergence rate of the system to the sliding surface. For suppressing the chattering, the symbolic function in the ideal sliding mode is replaced by the saturation function. To suppress the effect of model uncertainties and external disturbances, a double-loop recurrent fuzzy neural network is introduced to approximate and compensate system nonlinearities for the gyroscope sensor. At the same time, the double-loop recurrent fuzzy neural network can effectively accelerate the speed of parameter learning by introducing the adaptive mechanism. Simulation results indicate that the control system with the proposed controller is easily implemented, and it has higher tracking precision and considerable robustness to model uncertainties compared with the existing controllers.

A fuzzy neural network approximator with fast terminal sliding mode and its applications

2004 ◽  
Vol 148 (3) ◽  
pp. 469-486 ◽  
Author(s):  
Shuanghe Yu ◽  
Xinghuo Yu ◽  
Zhihong Man
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Sliding Mode ◽  
Terminal Sliding Mode ◽  
Fast Terminal Sliding Mode ◽  
Fuzzy Neural

Fractional-order nonsingular terminal sliding mode control via a disturbance observer for a class of nonlinear systems with mismatched disturbances

2020 ◽  
pp. 107754632092526
Author(s):  
Amir Razzaghian ◽  
Reihaneh Kardehi Moghaddam ◽  
Naser Pariz
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Fractional Order ◽  
Finite Time ◽  
Disturbance Observer ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Terminal Sliding Mode Control ◽  
Terminal Sliding Mode ◽  
Nonsingular Terminal Sliding Mode

This study investigates a novel fractional-order nonsingular terminal sliding mode controller via a finite-time disturbance observer for a class of mismatched uncertain nonlinear systems. For this purpose, a finite-time disturbance observer–based fractional-order nonsingular terminal sliding surface is proposed, and the corresponding control law is designed using the Lyapunov stability theory to satisfy the sliding condition in finite time. The proposed fractional-order nonsingular terminal sliding mode control based on a finite-time disturbance observer exhibits better control performance; guarantees finite-time convergence, robust stability of the closed-loop system, and mismatched disturbance rejection; and alleviates the chattering problem. Finally, the effectiveness of the proposed fractional-order robust controller is illustrated via simulation results of both the numerical and application examples which are compared with the fractional-order nonsingular terminal sliding mode controller, sliding mode controller based on a disturbance observer, and integral sliding mode controller methods.

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