Non-linear model order reduction for elastohydrodynamic lubrication simulations of polymer seals

Ischinger, F.; Bartel, Dirk; Brunk, Markus; Solovyev, Sergey

doi:10.1016/j.triboint.2019.105885

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…The goal of model order reduction is to compute an equivalent model which is simpler than the original complex systems and preserves the essential properties of the original system. The model diminution of higher order dynamical systems is a popular theme within the field of biological models (Javed and Ahmad, 2019; Snowden et al, 2017), control systems (Gautam et al, 2019; Kumar et al, 2016; Vasu et al, 2019), electromagnetic theory (Celo et al, 2005; Ng et al, 2020), mechanical engineering (Ischinger et al, 2019; Lin and Nikravesh, 2006; Veraszto et al, 2020), power systems (Al-Iedani and Gajic, 2020; Luo and Dhople, 2014; Wang and Long, 2020), chemical engineering (Nguyen et al, 2014, 2020; Tong et al, 2014) and so forth.…”

Section: Introductionmentioning

confidence: 99%

A novel order reduction method for linear dynamic systems and its application for designing of PID and lead/lag compensators

Prajapati

Prasad

2020

Transactions of the Institute of Measurement and Control

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This paper proposes a new model order reduction technology for the simplification of the complexity of large scale models. The proposed technique is focused on the Mihailov stability approach that guarantees the stability of the reduced model constrained that the complex system is stable. In this scheme, the denominator coefficients of the approximated simplified system are computed by using the Mihailov stability algorithm and the truncation method is used for the determination of coefficients of the numerator polynomial. The effectiveness and efficiency of the proposed approach are illustrated by comparing the step responses of the given system and approximated lower order models. The error indices such as integral square error (ISE), relative integral square error (RISE), integral absolute error (IAE) and integral time weighted absolute error (ITAE) are used as performance indices for comparing the proposed scheme with other existing standard reduced order modeling methods. The obtained reduced model is used for the designing of controllers for the original complex system. A new scheme for the determination of controllers is also proposed for the large scale models with help of reduced order modeling. The proposed technique is validated by applying it to an eighth order flexible-missile control system and a third order fuel control system. The simulation results show the dominance of the proposed methodologies over the latest model diminution techniques available in the literature.

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