Abstract
In this paper, a neural network adaptive sliding mode control is proposed for an MEMS triaxial gyroscope with unknown system nonlinearities. An input-output linearization technique is incorporated into the neural adaptive tracking control to cancel the nonlinearities, and the neural network whose parameters are updated from the Lyapunov approach is used to perform the linearization control law. The sliding mode control is utilized to compensate the neural network's approximation errors. The stability of the closed-loop system can be guaranteed with the proposed adaptive neural sliding mode control. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive neural sliding mode control scheme.
Highlights
A gyroscope is a commonly used sensor for measuring angular velocity in many areas of application, such as navigation, homing and control stabilization
The performance of the MEMS gyroscope is deteriorated by the effects of time‐varying parameters as well as noise sources, quadrature errors, parameter variations and external disturbances, which generate a frequency of oscillation mismatch between the two vibrating axes
This paper focuses on the design of an adaptive neural sliding mode control based on input‐output linearization
Summary
A gyroscope is a commonly used sensor for measuring angular velocity in many areas of application, such as navigation, homing and control stabilization. Much research has been done to apply intelligent control approaches such as neural networks and fuzzy controls that do not require mathematical models and have the ability to approximate nonlinear systems. Adaptive fuzzy sliding mode control schemes have been developed for robotic manipulators [12,13]. Horng [15] proposed a neural adaptive tracking control for a DC motor with unknown system nonlinearities where neural network approximation errors are compensated for by using the sliding mode scheme. Neural network sliding mode control approaches have been developed for robotic manipulators [18,19]. A robust adaptive neural sliding mode tracking control approach is presented for a MEMS gyroscope.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
