Embedded estimation of fault parameters in an unmanned aerial vehicle

Samar, S.; Gorinevsky, D.; Boyd, Stephen

doi:10.1109/cacsd-cca-isic.2006.4777161

Cited by 9 publications

(9 citation statements)

References 13 publications

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“…For further analysis, let us re-write the problem (13)- (14) in the matrix form using notation (16), (17).…”

Section: X(t + 1) = Ax(t) + U(t)mentioning

confidence: 99%

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Optimal Estimate of Monotonic Trend with Sparse Jumps

Gorinevsky

2007

2007 American Control Conference

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Abstract-This paper discusses a problem for recovering an underlying trend from noisy data. The key assumption is that the trend is monotonic, e.g., reflects accumulation of irreversible system deterioration. The trend is obtained as a maximum a posteriori probability estimate. The overall problem setup is related to α-β filter and Hodrick-Prescott filter. The main difference is that instead of a Gaussian process noise, a onesided exponentially distributed noise is assumed. The batch estimate is a solution to a Quadratic Programming problem. The approach works exceptionally well for piece-wise linear trends that have a small number of jumps in the trended variable or its increase rate. Theoretical analysis justifies the sparsity properties for the jumps in the solution.

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“…For further analysis, let us re-write the problem (13)- (14) in the matrix form using notation (16), (17).…”

Section: X(t + 1) = Ax(t) + U(t)mentioning

confidence: 99%

“…This paper extends an earlier conference paper [9], where trending based on the monotonic walk model was introduced. For related work (outside of the scope of this paper) see [17] and the references there. The goals and contribution of this paper are two-fold.…”

Section: Introductionmentioning

confidence: 99%

Optimal Estimate of Monotonic Trend with Sparse Jumps

Gorinevsky

2007

2007 American Control Conference

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“…The computation time can be further reduced by 1-2 orders of magnitude by developing specialized solvers." [26] Such efficiency in our view can lead to ground breaking applications in online accelerator monitoring. Examination of the computational efficiency of the fault estimation is a key objective of the Phase I project.…”

Section: -Optimization Problem For Dimension Reductionmentioning

confidence: 99%

Optimal Model-Based Fault Estimation and Correction for Particle Accelerators and Industrial Plants Using Combined Support Vector Machines and First Principles Models

Sayyarrodsari¹,

Schweiger²

2010

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“…When estimating monotonic signals, the filtering approach based on constrained optimization provides a substantial improvement over standard linear filtering methods. Some applications of optimization-based estimation based on monotonic walk models are discussed in [27], [54]. The source of monotonicity considered there is an irreversible nature of faults in the system.…”

Section: Introductionmentioning

confidence: 99%

Optimal Estimation of Deterioration From Diagnostic Image Sequence

Gorinevsky

Kim

Beard

et al. 2009

IEEE Trans. Signal Process.

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Abstract-This paper considers estimation of pixel-wise monotonic increasing (or decreasing) data from a time series of noisy blurred images. The motivation comes from estimation of mechanical structure damage that accumulates irreversibly over time. We formulate a Maximum A posteriory Probablity (MAP) estimation problem and find a solution by direct numerical optimization of a log-likelihood index. Spatial continuity of the damage is modeled using a Markov Random Field (MRF). The MRF prior includes the temporal monotonicity constraints. We tune the MRF prior, using a spatial frequency domain loopshaping technique to achieve a tradeoff between noise rejection and signal restoration properties of the estimate.The MAP optimization is a large-scale Quadratic Programming (QP) problem that could have more than a million of decision variables and constraints. We describe and implement an efficient interior-point method for solving such optimization problem. The method uses a preconditioned conjugate gradient method to compute the search step. The developed QP solver relies on the special structure of the problem and can solve the problems of this size in a few tens of minutes, on a PC.The application example in the paper describes structural damage images obtained using a Structural Health Monitoring (SHM) system. The damage signal is distorted by environmental temperature that varies for each acquired image in the series. The solution for the experimental data is demonstrated to provide an excellent estimate of the damage accumulation trend while rejecting the spatial and temporal noise.Index Terms-Optimal estimation, spatio-temporal filtering, regularization, interior-point method, isotonic regression, Markov Random Field.

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Embedded estimation of fault parameters in an unmanned aerial vehicle

Cited by 9 publications

References 13 publications

Optimal Estimate of Monotonic Trend with Sparse Jumps

Optimal Estimate of Monotonic Trend with Sparse Jumps

Optimal Model-Based Fault Estimation and Correction for Particle Accelerators and Industrial Plants Using Combined Support Vector Machines and First Principles Models

Optimal Estimation of Deterioration From Diagnostic Image Sequence

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