Reduced-Order Filter Design for Discrete-Time Systems Corrupted with Multiplicative Noise

Stoica, Adrian–Mihail; Barbelian, Mihai; Pana, Valentin; Dragasanu, Claudiu

doi:10.2514/1.48736

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…Another novelty of the paper is that the dynamic model which states are estimated, includes both additive white noise components, well-known in the classical Kalman filtering and multiplicative (state-dependent) noisy terms induced by the inertial sensors measurements. Linear reduced order filters for discrete-time models including multiplicative noise have been developed based on H ∞ -norm minimization techniques in [8]. The present paper is organized as follows: in the next section the kinematic equations of the satellite are presented together with the measurements model showing that their linear approximation is in fact a stochastic system corrupted both with additive and state-dependent (multiplicative) noise.…”

Section: Introductionmentioning

confidence: 99%

A New Kalman-Type Approach for Satellites Attitude Determination

Stoica

2014

AMM

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This paper presents a Kalman type method for attitude determination of satellites. It is shown that the linearized model describing the satellite kinematics may be expressed as a stochastic system corrupted with both additive and multiplicative white noise. For this class of stochastic models a hybrid Kalman filter is used to estimate the quaternion expressing the satellite attitude and the bias of the inertial measurement unit. By contrast with the classical Kalman filters, the hybrid filter used in this paper includes a continuous-time and a discrete-time component. The advantage is that it may provide a time varying estimation of the states between the sampling moments which usually are sparse in space applications. The theoretical developments is illustrated via a numerical case study.

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Section: Introductionmentioning

confidence: 99%

A New Kalman-Type Approach for Satellites Attitude Determination

Stoica

2014

AMM

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Adaptive control and signal processing literature survey (No. 20)

2010

Adaptive Control & Signal

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In order to keep the readers up-to-date, the journal will contain a list of recently published journal articles relevant to the fields of adaptive control and signal processing six times a year. This list is compiled from a wide range of journals. Please note that although the list has been broadly categorized, these classifications are by no means strict and are there to assist the reader. Please also note that inclusion in the list is not an endorsement of a paper's quality. If you have any suggestions or comments, please e-mail Erfu Yang at erfu.yang@eee.strath.ac.uk. ADAPTIVE SYSTEMSAbramovich Y, Frazer G, Johnson B. Iterative adaptive Kronecker MIMO radar beamformer: description and convergence analysis. IEEE Transactions on Signal Processing 2010; 58(7):3681-3691. Badwe A, Singh A, Patwardhan S, Gudi R. A constrained recursive pseudo-linear regression scheme for on-line parameter estimation in adaptive control. Journal of Process Control 2010; 20(5):559-572. Cassimatis N, Bignoli P, Bugajska M, Dugas S, Kurup U, Murugesan A, Bello P. An architecture for adaptive algorithmic hybrids. IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetic 2010; 40(3):903-914. Cheah C, Hou S, Zhao Y, Slotine J-J. Adaptive vision and force tracking control for robots with constraint uncertainty. IEEE/ASME Transactions on Mechatronics 2010; 15(3): 389-399. Cheah C, Liu C, Slotine J. Adaptive Jacobian vision based control for robots with uncertain depth information. Automatica 2010; 46(7):1228-1233. De Maio A, Conte E. Adaptive detection in Gaussian interference with unknown covariance after reduction by invariance. IEEE Transactions on Signal Processing 2010; 58(6):2925-2934. Fei J. Robust adaptive vibration tracking control for a micro-electro-mechanical systems vibratory gyroscope with bound estimation. control allocation for non-linear systems with internal dynamics. IET Control Theory and Applications 2010; 4(6):909-922. Liu L, Xie X-J. Decentralized adaptive stabilization for interconnected systems with dynamic input-output and nonlinear interactions. Automatica 2010; 46(6):1060-1067. Malloci I, Daafouz J, Iung C. Stability and stabilization of two time scale switched systems in discrete time. IEEE Transactions on Automatic Control 2010; 55(6):1434-1438. Mileounis G, Babadi B, Kalouptsidis N, Tarokh V. An adaptive greedy algorithm with application to nonlinear communications. IEEE Transactions on Signal Processing 2010; 58(6):2998-3007. Nguyen H-X, Nguyen H-H. Adaptive relaying in noncoherent cooperative networks. IEEE Transactions on Signal Processing 2010; 58(7):3938-3945. Pigg S, Bodson M. Adaptive algorithms for the rejection of sinusoidal disturbances acting on unknown plants. IEEE Transactions on Control Systems Technology 2010; 18(4): 822-836. Tucci M, Raugi M. Adaptive FIR neural model for centroid learning in self-organizing maps. IEEE Transactions on Neural Networks 2010; 21(6):948-960. Wang L, de Lamare R, Yukawa M. Adaptive reducedrank constrained constant modulus algorithms based on

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Full-order observer design for linear systems with unknown inputs

Lungu

2012

International Journal of Control

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Reduced-Order Filter Design for Discrete-Time Systems Corrupted with Multiplicative Noise

Cited by 4 publications

References 7 publications

A New Kalman-Type Approach for Satellites Attitude Determination

A New Kalman-Type Approach for Satellites Attitude Determination

Adaptive control and signal processing literature survey (No. 20)

Full-order observer design for linear systems with unknown inputs

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