Real-time state observers based on multibody models and the extended Kalman filter

Cuadrado, Javier; Dopico, Domingo Calvo; Barreiro, Antonio; Delgado, Emma

doi:10.1007/s12206-009-0308-5

Cited by 42 publications

(45 citation statements)

References 6 publications

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“…Assuming that other parameters are constant, the influence of these parameters on the fatigue strength conforms to a linear law approximately. Bringing source data into factor space, the corresponding grey relational grade can be obtained by equations (17)- (21).…”

Section: Parametric Treatment Of Each Impact Factormentioning

confidence: 99%

“…e statistical deduction of small-sample discrete data is used to obtain the transformed data by multisource data acquirement and fusion. e common data fusion algorithm includes the grey relational method, Kalman filter method, adaptive weighted method, D-S evidence theory, and neural network theory [20][21][22][23][24]. ese algorithms were mainly applied to signal analysis and fault diagnosis at first and recently used in the assessment of fatigue strength and residual life [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

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Fatigue Strength Evaluation for Remanufacturing Impeller of Centrifugal Compressor Based on Modified Grey Relational Model

Sun

Shi

et al. 2020

Advances in Materials Science and Engineering

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The fatigue strength, as the essential basis of residual life evaluation, is required to be obtained timely for remanufacturing. Since impeller damage is characterized with very-high-cycle fatigue (VHCF), it is difficult to directly test the strength data. The transformation method of multisource strength data is proposed to predict fatigue strength for impeller based on grey relational theory. The multisource strength data, as factor space, primarily include available existing experimental data and operating data, while the strength data of the remanufacturing impeller are taken as target data. The fatigue strength model of material and component are presented to analyze the influence factors of remanufacturing target strength. And similar material provides a theoretical basis for selecting reference data reasonably. Considering the correlation and difference between available data and target data, the grey relational function is established, and the correction function of the target residual is brought forward to reduce the transformation deviation. The entropy-weight theory is implemented to determine the different impacts of multisource data on target strength. A test case, predicting the unknown impeller fatigue strength with various impellers, is applied to validate the proposed transformation method, and the results show that the predicted strength data are consistent with the experimental data well.

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Section: Parametric Treatment Of Each Impact Factormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fatigue Strength Evaluation for Remanufacturing Impeller of Centrifugal Compressor Based on Modified Grey Relational Model

Sun

Shi

et al. 2020

Advances in Materials Science and Engineering

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“…In the previous works, the observer equations had been obtained through straightforward combination of the first set of Equation (2) and the integrator equations (trapezoidal rule), since, once the Jacobians A and C are determined, the Kalman gain can be calculated as expressed in the second and third sets of Equation (2). In this way, the resulting observer equations are of size 2 .…”

Section: The Observer Dynamic Equationsmentioning

confidence: 99%

“…In a first previous work [2], the authors selected the two dynamic formulations which were found to better fit the structure required by the EKF, and compared them: a state-space reduction method known as matrix-R method, and a penalty method. It was concluded that the matrix-R method was faster and more accurate than its counterpart.…”

Section: Introductionmentioning

confidence: 99%

Automotive observers based on multibody models and the extended Kalman filter

et al. 2011

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This work is part of a project aimed to develop automotive real-time observers based on detailed multibody models and the extended Kalman filter (EKF). In previous works, a four-bar mechanism was studied to get insight into the problem. Regarding the formulation of the equations of motion, it was concluded that the state-space reduction method known as matrix-R is the most suitable one for this application. Regarding the sensors, it was shown that better stability, accuracy and efficiency are obtained as the sensored magnitude is a lower derivative and when it is a generalized coordinate of the problem. In the present work, the automotive problem has been already addressed, through the selection of a Volkswagen Passat as a case-study. A model of the car containing fourteen degrees of freedom has been developed. The observer algorithm that combines the equations of motion and the integrator has been reformulated so that duplication of the problem size is avoided, in order to improve efficiency. A maneuver of acceleration from rest and double lane change has been defined, and tests have been run for the "prototype", the "model" and the "observer", all the three computational, with the model having 100 kg more than the prototype. Results have shown that good convergence is obtained, but the computational cost is high, still far from real-time performance.

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“…3.5. Estimator design 3.5.1 Estimation of the state variables and the road disturbance velocity In this paper, a Kalman filter [20][21][22][23][24] is introduced to estimate the necessary state variables ( , …”

Section: Optimal Values Of C Sky and C Vmentioning

confidence: 99%

Road-frequency adaptive control for semi-active suspension systems

Nguyen

Hong

Park

2010

Int. J. Control Autom. Syst.

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In this paper, a road-frequency adaptive control for semi-active suspension systems is investigated. The control aims to improve the vehicle suspension performance (ride comfort and wheel handling) for all frequency regions of road disturbances. In order to achieve this aim, the control law is extended from the conventional skyhook control, and the controller gains are scheduled for various frequency regions of road disturbances. By using the data measured from a relative displacement sensor, a state estimator based on a Kalman filter for estimating the required state variables is designed. Road disturbance frequencies are estimated by using a first order zero-crossing algorithm. The efficiency of the proposed control is shown through numerical simulations.

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Real-time state observers based on multibody models and the extended Kalman filter

Cited by 42 publications

References 6 publications

Fatigue Strength Evaluation for Remanufacturing Impeller of Centrifugal Compressor Based on Modified Grey Relational Model

Fatigue Strength Evaluation for Remanufacturing Impeller of Centrifugal Compressor Based on Modified Grey Relational Model

Automotive observers based on multibody models and the extended Kalman filter

Road-frequency adaptive control for semi-active suspension systems

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