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In the appendix we present an analytical model for system performance and compare it to our experimental results.
Using an analytical model, the system is explained through close investigation of the resonance modes.
For this reason, most ULPC planning methods in the literature rely on simple analytical models for system performance assessment.
Both analytical modeling and a system identification of the vehicle are described, issues of modal representation and model reduction are covered, and a robust controller design is motivated and explained.
One of the challenging tasks in the analytical modeling of galloping systems is the representation of the galloping force.
By considering dual cycle coupled with lower mid-point S/R crane dwell-point policy, Xu et al. (2017) has developed a continuous travel-time model for DC in 3D compact storage system; then, he has used the analytical models to optimise system dimensions.
This study presents a methodology for the on-line identification of nonlinear hysteretic systems where not only the parameters of the system are unknown but also the nature of the analytical model describing the system is not clearly established.
We describe an analytical model of the system under consideration and present two mathematical approaches to derive solutions for any system configuration and deployment, along with an adaptive feedback-based solution.
An accurate, analytical model of the system is obtained by using the electromagnetic theory to estimate the electromagnetic forces, induced in the system.
Analytical model of the system was then developed and verified by full-scale shaking table test.
An analytical model of the system is developed in order to predict the experimental findings.
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