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Initial alignment for nonlinear inertial navigation systems with multiple disturbances based on enhanced anti-disturbance filtering. (English) Zbl 1256.93106
Summary: Initial alignment for Inertial Navigation System (INS) has been widely used in practice under the assumption of Gaussian noises. In most previous works, nonlinear dynamics was ignored and the disturbances were merged into either a Gaussian or norm-bounded variable, where the Kalman filtering or robust filtering can be applied, respectively. In this article, the unmodeled nonlinear dynamics, drifts, parametric uncertainties, as well as other disturbances are considered simultaneously and are formulated into different types of uncertain disturbances described by the exo-system, stochastic and norm-bounded variables, respectively. A nonlinear initial alignment approach for INS is first presented based on a new disturbance attenuation and rejection filtering scheme against multiple disturbances. The INS error model with both nonlinear dynamics and multiple disturbances is established and the initial alignment problem is transformed into a robust nonlinear filter design problem for a class of nonlinear systems with multiple disturbances. In the proposed composite filtering approach, the drift filter is designed to estimate and compensate the inertial sensor drift. Mixed \(H_2/H_\infty\) filtering is designed to optimize the estimation error and attenuate the norm-bounded uncertain disturbances, respectively. Simulations for ground stationary base initial alignment of an INS are provided. Comparisons show that the concerned INS has the enhanced disturbance rejection and attenuation performance.

93E11 Filtering in stochastic control theory
93B35 Sensitivity (robustness)
93C73 Perturbations in control/observation systems
Full Text: DOI
[1] DOI: 10.1109/TAES.2006.1603406 · doi:10.1109/TAES.2006.1603406
[2] Cao, SY and Guo, L. 2009. Fault Diagnosis with Disturbance Rejection Performance Based on Disturbance Observer. Proceedings of IEEE Conference on Decision Control. 2009. pp.6947–6951. Shanghai, China
[3] DOI: 10.1016/j.ast.2011.04.006 · doi:10.1016/j.ast.2011.04.006
[4] DOI: 10.1109/7.543871 · doi:10.1109/7.543871
[5] Farrell JA, The Global Positioning System & Inertial Navigation (1999)
[6] DOI: 10.1016/j.automatica.2006.05.030 · Zbl 1222.93215 · doi:10.1016/j.automatica.2006.05.030
[7] DOI: 10.1109/TSP.2007.900154 · Zbl 1390.93169 · doi:10.1109/TSP.2007.900154
[8] DOI: 10.1002/0470099720 · doi:10.1002/0470099720
[9] DOI: 10.1017/S0373463303002261 · doi:10.1017/S0373463303002261
[10] DOI: 10.1002/rnc.978 · Zbl 1078.93030 · doi:10.1002/rnc.978
[11] Guo L, Stochastic Distribution Control System Design: A Convex Optimization Approach (2009)
[12] DOI: 10.1007/s00034-005-0311-8 · Zbl 1106.93052 · doi:10.1007/s00034-005-0311-8
[13] DOI: 10.1017/S0373463310000214 · doi:10.1017/S0373463310000214
[14] DOI: 10.1109/7.640292 · doi:10.1109/7.640292
[15] DOI: 10.2514/2.4904 · doi:10.2514/2.4904
[16] DOI: 10.1109/TSMCA.2008.2010137 · doi:10.1109/TSMCA.2008.2010137
[17] DOI: 10.1016/j.jfranklin.2009.09.003 · Zbl 1185.93135 · doi:10.1016/j.jfranklin.2009.09.003
[18] DOI: 10.1002/(SICI)1097-4563(199902)16:2<81::AID-ROB2>3.0.CO;2-9 · Zbl 0925.70003 · doi:10.1002/(SICI)1097-4563(199902)16:2<81::AID-ROB2>3.0.CO;2-9
[19] Rogers RM, Applied Mathematics in Integrated Navigation Systems,, 3. ed. (2007)
[20] Scherzinger B, Proceedings of IEEE Position Location and Navigation Symposium pp 477– (1996)
[21] DOI: 10.1016/j.ast.2009.04.002 · doi:10.1016/j.ast.2009.04.002
[22] Wang LX, Acta Aeronautical & Astronautica Sinica 29 pp 102– (2008)
[23] DOI: 10.1080/00207170802455339 · Zbl 1168.93322 · doi:10.1080/00207170802455339
[24] DOI: 10.1109/TSP.2005.855109 · Zbl 1370.93109 · doi:10.1109/TSP.2005.855109
[25] DOI: 10.1109/TAES.2004.1337455 · doi:10.1109/TAES.2004.1337455
[26] DOI: 10.1007/s10291-006-0046-4 · doi:10.1007/s10291-006-0046-4
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