Automatic EKF Tuning for UAS Path Following in Turbulent Air
By using two simultaneously working Extended Kalman Filters, a procedure is implemented in order to perform in a fully autonomous way the path following in turbulent air. To guarantee the robustness of the proposed algorithm, an automatic tuning procedure is proposed to determine optimal values of Process and Measurement Noise statistics. Such a procedure is based on both the characteristics of the disturbances and the desired flight path; in particular, a specific performance index is applied to tune filters. In this way control laws are adapted to the flight condition and these lead to an optimal path-following. This research represents an upload of previous papers. It allows eliminating the time expensive trial and error procedure usually employed to tune Extended Kalman Filters. Obviously, procedure results are optimal for ever flight condition.
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Mitsutake, K., Higashino, S., Evaluation of an A*-EC Hybrid Path Planning Method for UAVs Using Real-Time Hardware-in-the-Loop Simulation, (2013) International Review of Aerospace Engineering (IREASE), 6 (1), pp. 40-47.
Sigurd K., How J., UAV Trajectory Design using Total field Collision Avoidance, AIAA Guidance, navigation and Control Conference and Exhibit (2013), Austin, TX, USA, 2013
Wilburn, J., Perhinschi, M., Wilburn, B., Enhanced Modified Voronoi Algorithm for UAV Path Planning and Obstacle Avoidance, (2013) International Review of Aerospace Engineering (IREASE), 6 (1), pp. 54-63.
Bousson, K., Gameiro, T., A Quintic Spline Approach to 4D Trajectory Generation for Unmanned Aerial Vehicles, (2015) International Review of Aerospace Engineering (IREASE), 8 (1), pp. 1-9.
Benzerrouk, H., Salhi, H., Nebylov, A., Non-Gaussian Sensor Fusion Analysis with “Gaussian Mixture and Adaptive” Based Cubature Kalman Filtering for Unmanned Aerial Vehicle, (2013) International Review of Aerospace Engineering (IREASE), 6 (6), pp. 264-277.
Nelson D., Barber D., McLain T., Beard R., Vector fields path following for miniature air vehicles, IEEE T on Robotics, Vol. 23(3), (2007), pp. 519-529
Brezoescu A., Espinoza T., Castillo P., Lozano R., Adaptive Trajectory Following for a Fixed-Wing UAV in Presence of Crosswind, Journal of Intelligent Robot System, Vol. 69,(2013), pp. 257-271
Liu C., McAree O., Chen W.-H., Path Following Control for Small fixed-wing unmanned aerial vehicles under wind disturbances, International Journal of Robust and Nonlinear Control, Vol. 23, (2013), pp. 1682-1698
Smith J., Su J., Liu C., Chen W.-H., Disturbance Observer Based Control with Anti-Windup Applied to a Small Fixed-Wing UAV for Disturbance Rejection, Journal of Intelligent Robot System: Theory and Applications, Vol. 88 (2-4) (2017), pp. 329-346
Liu C., Chen W.-H., Disturbance Rejection Flight Control for Small Fixed-Wing Unmanned Aerial Vehicles, Journal of Guidance, Control and Dynamics, Vol.39 (12) (2016), pp. 2804-2813
Grillo, C., Montano, F., An EKF Based Method for Path Following in Turbulent Air, (2017) International Review of Aerospace Engineering (IREASE), 10 (1), pp. 1-6.
T. D. Powell, Automated Tuning of an Extended Kalman Filter Using Downhill Simplex Algorithm, Journal of Guidance, Control and Dynamics, Vol. 25 (5), (2002), pp. 901-908
M. Saha, R. Ghosh, B. Goswami, Robustness and Sensitivity Metrics for Tuning the Extended Kalman Filter, IEET Transactions on Instrumentation and Measurement, Vol. 63 (4) (2014), pp. 964-971
M. Saha, B. Goswami, R. Gosh, Two novel metrics for determining the tuning parameters of the Kalman filter, Proceeding of ACODS, 2012, Bangalore, India, pp. 1-8
H. Al-Ghossini, F. Locment, M. Sechilariu, L. Gagneur, C. Forgez, Adaptive-tuning of extended Kalman fiter used for small scale wind generator control, Renewable Energy, Vol. 85 (2016), pp- 1237-1245
S. Bolognani, L. Tubiana, M. Zigliotto, Extended Kalman Filter Tuning in Sensorless PMSM Drives, IEEE Transactions on Industry Applications, Vol. 39 (6) (2003), pp. 1741-11747
K. Rapp, P. O. Nayman, Optimization of Extended Kalman Filter for Improved Thresoholding Performance, Proccedings of IFAC Control Systems Design, Bratislava, Slovak Republic, 2003, pp. 119-124
F. Jiangchen, Y. Sheng, Study on Innovation Adaptive EKF for in-flight alignment of airborne POS, IEEE Transaction on Instrumentation and Measurement, Vol. 60 (4) (2011), pp. 1378-1388
Grillo C., Montano F., Optimal Flight Path Determination in Turbulent Air: A Modified EKF Approach, AerotecnicaMissili&Spazio, The Journal of Aerospace Science, Technology and Systems, Vol. 96 (4) (2017), pp.216-222
Welch G., Bishop G., An Introduction to the Kalman Filter (TR 95041, Department of Computer Science, University of North Carolina at Chapel Hill, 2004)
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