Nonlinear Robust Bias Observer for MEMS Gyros Using Noninertial Attitude Sensor Measurement

In robotic applications, the dynamics sensitivities of commercial-grade micro-electro-mechanical system (MEMS) gyros often exhibit uncertainties that cannot be accurately modeled by linear drift. To address the estimation of these uncertain biases, we propose a novel nonlinear robust bias observer (NRBO) in this article. Unlike existing nonlinear observers for attitude and gyro bias, our proposed method incorporates a dynamics-sensitive gyro bias estimation approach, achieved through the synthesis of the attitude-angular rate nonlinear dynamic coupling (AARNDC) term and the attitude-linear coupling (ALC) term. We highlight the potential advantages of our proposed method, including the asymptotic stability of the NRBO and its robustness against MEMS gyro bias instability, enabled by a rational design of the AARNDC and ALC terms. In addition to gyro bias estimation, we present the attitude estimation within the NRBO framework. Field experimental results, conducted with a cable-driven parallel robot, demonstrate the robustness of the proposed NRBO against bias instability measurement noise. Moreover, the results highlight its superior accuracy when compared with the invariant extended Kalman filter and nonlinear navigation observer methods.