Friction coefficient estimation using an unscented Kalman filter

Most of the advanced nonlinear control strategies reported in the literature for underactuated mechanisms, such as overhead cranes, require the knowledge of all state variables. For cranes, the state vector includes variables related to load sway and its velocity. The flatness property of crane-like systems can be exploited to solve both the motion planning and the tracking problems so that the load (whose coordinates are included in the set of the flat outputs) exponentially follows a rapid reference trajectory. However, unmodelled friction phenomena and limitations on the direct measurement of sway related state variables usually impede the practical implementation of flatness-based control laws. This paper proposes the use of an adaptive unscented Kalman filter to estimate friction forces and unmeasured state variables. The convergence of the filter is improved using a novel technique, called condition-based selective scaling. The performance of the suggested scheme is verified through a set of computer simulations on a 2D overhead crane system.

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“…Similar to the joint parameter-state estimation approach suggested in [52], [53], the extended model with the augmented state vector,…”

Section: A Model Description For Kalman Filteringmentioning

confidence: 99%

Tracking Control of Overhead Crane Using Output Feedback With Adaptive Unscented Kalman Filter and Condition-Based Selective Scaling

et al. 2021

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“…The bridge circuits q1 and q2, which consist of the strain gauges 1a to 7a and 1a' to 7a' are for measuring Q. al., 2014;Murata, et al, 2018aMurata, et al, , 2018bHeckman, et al, 2019). The observer approaches have common issues: how to design the plant model and how to decide the plant parameters.…”

Section: Introductionmentioning

confidence: 99%

Measurement method for longitudinal displacement of wheel/rail contact point using strain gauges put on wheels

Hondo

Noguchi

2020

Mechanical Engineering Journal

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This paper describes a measurement method for longitudinal displacement of wheel/rail contact point in a railway vehicle using a wheelset to measure the wheel/rail contact forces, which is generally used for the sake of the running safety evaluation in Japan. The clarification of phenomenon related to the wheel/rail contact has very important role to discuss the curving performance and the running safety of railway vehicles. The longitudinal displacement of the contact point is related to the wheelset angle of attack, which is related to the steering performance of the wheelset. The authors propose algorithms to extract informations about the contact point from the cyclic signal of the strain gauges that are put on the wheel to measure the contact forces. Experiments on roller rigs were carried out to evaluate the reliability and the accuracy of the proposed algorithm. The running tests were also carried out to demonstrate the applicability of the proposed algorithm to the real condition used. Those test results show that the measurement result using proposed algorithm is reliable as a longitudinal displacement of the contact point.

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“…1 that unscented Kalman filter (UKF), which is also used in this study, is generally considered to estimate wheel–rail friction coefficients in the railway industry. 2,3…”

Section: Introductionmentioning

confidence: 99%

An unscented Kalman filter-based rolling radius estimation methodology for railway vehicles with traction

Onat

Voltr

Lata

2017

Proceedings of the Institution of Mechanical Engineers, Part F:

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Monitoring the conditions of railway vehicle systems plays an important role in the maintenance of safety and performance of railway vehicles. Rolling radius is one of the properties that should be monitored continuously for the predictive maintenance of a railway vehicle since it changes with time due to wheel wear. In this study, a model-based condition monitoring methodology, which is based on an unscented Kalman filter, is proposed. The model includes the torsional dynamics of an independently rotating tram wheel with a traction motor and a contact model. The rolling radius is estimated by considering the traction effort of the motor and the angular velocity measurements. The proposed methodology is tested on a tram wheel test stand (roller rig), which has a wheel on roller configuration. First, a mathematical model is validated by the measurements taken from the test stand. Second, the unscented Kalman filter is applied as a parameter estimator. The results demonstrate that the proposed scheme is a promising option to be used in the predictive condition monitoring of the wheel profile for traction vehicles.

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Friction coefficient estimation using an unscented Kalman filter

Cited by 28 publications

References 15 publications

Tracking Control of Overhead Crane Using Output Feedback With Adaptive Unscented Kalman Filter and Condition-Based Selective Scaling

Tracking Control of Overhead Crane Using Output Feedback With Adaptive Unscented Kalman Filter and Condition-Based Selective Scaling

Measurement method for longitudinal displacement of wheel/rail contact point using strain gauges put on wheels

An unscented Kalman filter-based rolling radius estimation methodology for railway vehicles with traction

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