For fixed-wing micro air vehicles, the attitude determination is usually produced by the horizon/Global Navigation Satellite System (GNSS) in which the GNSS provides yaw…
For fixed-wing micro air vehicles, the attitude determination is usually produced by the horizon/Global Navigation Satellite System (GNSS) in which the GNSS provides yaw estimates, while roll and pitch are computed using horizon sensors. However, the attitude determination has been independently obtained from the two sensors, which will result in insufficient usage of data. Also, when implementing attitude determination algorithms on embedded platforms, the computational resources are highly restricted. This paper aims to propose a computationally efficient linear Kalman filter to solve the problem.
The observation model is in the form of a least-square optimization composed by GNSS and horizontal measurements. Analytical quaternion solution along with its covariance is derived to significantly speed up on-chip computation.
The reconstructed attitude from Horizon/GNSS is integrated with quaternion kinematic equation from gyroscopic data that builds up a fast linear Kalman filter. The proposed filter does not involve coupling effects presented in existing works and will be more robust encountering bad GNSS measurements.
Electronic systems are designed on a real-world fixed-wing plane. Experiments are conducted on this platform that show comparisons on the accuracy and computation execution time of the proposed method and existing representatives. The results indicate that the proposed algorithm is accurate and much faster computation speed in studied scenarios.
Extended from the classic Rayleigh damping model in structural dynamics, the Caughey damping model allows the damping ratios to be specified in multiple modes while…
Extended from the classic Rayleigh damping model in structural dynamics, the Caughey damping model allows the damping ratios to be specified in multiple modes while satisfying the orthogonality conditions. Despite these desirable properties, Caughey damping suffers from a few major drawbacks: depending on the frequency distribution of the significant modes, it can be difficult to choose the reference frequencies that ensure reasonable values for all damping ratios corresponding to the significant modes; it cannot ensure all damping ratios are positive. This paper aims to present a constrained quadratic programming approach to address these issues.
The new method minimizes the error of the structural displacement peak based on the response spectrum theory, while all modal damping ratios are constrained to be greater than zero.
Several comprehensive examples are presented to demonstrate the accuracy and effectiveness of the proposed method, and comparisons with existing approaches are provided whenever possible.
The proposed method is highly efficient and allows the damping ratios to be conveniently specified for all significant modes, producing optimal damping coefficients in practical applications.