The compensation of nonlinear thermal bias drift of resonant rate sensor (RRS) using fuzzy logic

In this paper, our attention is focused on the compensation of the nonlinear thermal bias (zero-rate-output) drift of RRS (Resonant Rate Sensor), which originates from a number of sources, including manufacturing tolerances, material inhomogeneity and inevitable mechanical characteristic variation of the cylinder with temperature. Motivated by the capability of fuzzy logic in managing nonlinearity, the nonlinearity of bias was represented by Takagi-Sugeno (TS) fuzzy model over the entire range of operating temperature. Then, the fuzzy model was directly used for compensation of nonlinear bias drift by subtracting the estimated output from the raw data of RRS. By doing this, we can guarantee the robust (against temperature variations) sensor performance throughout entire operating temperature ranges