Abstract
In this paper, an actor critic neural network-based adaptive control scheme for micro-electro-mechanical system (MEMS) gyroscopes suffering from multiresource disturbances is proposed. Faced with multiresource interferences consisting of parametric uncertainties, strong couplings between axes, Coriolis forces, and variable external disturbances, an actor critic neural network is introduced, where the actor neural network is employed to estimate the packaged disturbances and the critic neural network is utilized to supervise the system performance. Hence, strong robustness against uncertainties and better tracking properties can be derived for MEMS gyroscopes. Aiming at handling the nonlinearities inherent in gyroscopes without analytically differentiating the virtual control signals, dynamic surface control (DSC) rather than backstepping control method is employed to divide the 2nd order system into two 1st order systems and design the actual control policy. Moreover, theoretical analyses along with simulation experiments are conducted with a view to validate the effectiveness of the proposed control approach.
Highlights
Owing to the microvolume, easy integration, and mass production, micro-electro-mechanical system (MEMS) gyroscopes are indispensable angular rate sensors in a myriad of areas including inertial guidance, aerospace, and national defense industry [1,2,3,4,5]
Our objective is to devise a control policy u based on ACNNs and dynamic surface control (DSC) schemes, which is capable of driving the output states of MEMS gyroscopes xp to track the reference signal yr [yr1, yr2]T as accurately as possible, in the existence of multisource interferences, i.e., F
By combining an actor neural networks (NNs) with a critic NN, the packaged disturbances can be effectively suppressed and system performance can be supervised at the same time, such that better tracking properties and stronger robustness against unknown dynamics can be guaranteed. rough inserting a first-order filter between the displacement and velocity loops of MEMS
Summary
Easy integration, and mass production, micro-electro-mechanical system (MEMS) gyroscopes are indispensable angular rate sensors in a myriad of areas including inertial guidance, aerospace, and national defense industry [1,2,3,4,5]. MEMS gyroscopes are inherently accounted for strong uncertainties and nonlinearities, rendering the high-precision control a challenging issue. Aiming at reducing the effects of uncertainties and enhancing system behaviours, several advanced schemes have been devised, such as neural networks (NNs) [6,7,8], extended state observers (ESOs) [9], and fuzzy logic systems (FLSs) [10], where the packaged disturbances are online estimated and compensated in the control policy. It is meaningful to devise a control scheme capable of recovering unknown interferences and supervising system tracking properties at the same time
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
