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Sliding mode observer to estimate both the attitude and the gyro-bias by using low-cost sensors

机译:滑模观察器通过使用低成本传感器来估计姿态和陀螺仪偏向

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This paper presents a nonlinear observer algorithm for attitude estimation that improves the quality of measures obtained by using low-cost inertial measurements (IMU). It is based on sliding mode observer that provides both the estimates of the gyro-bias and the actual attitude of the rigid body. The algorithm was developed in order to address the well-known problem of the weak dynamics of the tilt sensors and magnetometers, which can be modeled by low pass filters, and of the measurement bias of the gyros. In its design the observer uses the real measurements given by the low-cost attitude sensors (inclinometers and magnetometers) and the gyros, the filters modeling the sensors and the kinematics equation of the rigid body. The asymptotic convergence of the estimation of the attitude and bias-gyros was proven using Lyapunov stability method. The effectiveness of the algorithm has been shown from experimental tests using a rotary platform equipped with several sensors with axes of rotation coincide with orientation of the rigid body. Also, tests for comparison with a linear complementary filter are given.
机译:本文提出了一种用于姿态估计的非线性观测器算法,该算法提高了使用低成本惯性测量(IMU)获得的测量的质量。它基于滑模观察器,提供了陀螺仪偏向的估计值和刚体的实际姿态。开发该算法是为了解决众所周知的倾斜传感器和磁力计的弱动力学问题(可以通过低通滤波器建模)以及陀螺仪的测量偏差。观察者在其设计中使用了低成本姿态传感器(测斜仪和磁力计)和陀螺仪,对传感器建模的滤波器以及刚体的运动学方程式给出的实际测量值。利用Lyapunov稳定性方法证明了姿态和偏置陀螺仪估计的渐近收敛性。该算法的有效性已通过使用配备了多个传感器的旋转平台的旋转试验的实验测试表明,旋转轴的旋转方向与刚体的方向一致。另外,给出了与线性互补滤波器进行比较的测试。

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