The fuzzy controller design for MEMS gyro stable platform

Abstract

Since a high sensor noise level will limit the gain of a PID controller, an adaptive Kalman filter (KF) has been designed to reduce the noise of MEMS gyro in a stable platform system, which has better performance than a FIR filters, Such as smaller phase lag and lower variance. By using the filtered gyro signal, a T-S fuzzy reasoning module has been constructed to adjust the PID coefficients adaptively. The simulation illustrates that the fuzzy-PID performs better than a classic PID when conquering the disturbance torque acting on platform frame.