Gyroscope Real-Time Control Using Kalman Nonlinear Controller and Neural Network Controller

— Gyroscope is a sensor by which angular velocity and angular position can be obtained. These information are analyzed to obtain the general position of the body based on calculations. Gyroscope is the main part of Inertial Guidance systems. In this paper, an neural network controller and Kalman filter simulator for a vibratory gyroscope with z axis equipped with MEMS. The neural network controller type is a multilayer perceptron. Stabilization and convergence are obtained after implementation of expected outputs system model. Using Kalman filter for simulating the system model and also using the reverse plant for implementing the neural network controller are new ideas in this report which has minimized fault well and network stabilization has been supplied as well.

Keywords:

Gyroscope , System model , Kalman filter , neural network