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  • 1
    Publication Date: 2013-08-31
    Description: This paper presents the results of modeling and system identification efforts on the NASA Large-Angle Magnetic Suspension Test Fixture (LAMSTF). The LAMSTF consists of a cylindrical permanent magnet which is levitated above a planar array of five electromagnets mounted in a circular configuration. The analytical model is first developed and open-loop characteristics are described. The system is shown to be highly unstable and requires feedback control in order to apply system identification. Limitations on modeling accuracy due to the effect of eddy-currents on the system are discussed. An algorithm is derived to identify a state-space model for the system from input/output data acquired during closed-loop operation. The algorithm is tested on both the baseline system and a perturbed system which has an increased presence of eddy currents. It is found that for the baseline system the analytic model adequately captures the dynamics, although the identified model improves the simulation accuracy. For the system perturbed by additional unmodeled eddy-currents the analytic model is no longer adequate and a higher-order model, determined through system identification, is required to accurately predict the system's time response.
    Keywords: Mechanical Engineering
    Type: Third International Symposium on Magnetic Suspension Technology; Part 2; 403-419; NASA-CP-3336-Pt-2
    Format: application/pdf
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  • 2
    Publication Date: 2018-06-05
    Description: This study is an experimental investigation of the robustness of various controllers designed for the Large Angle Magnetic Suspension Test Fixture (LAMSTF). Both analytical and identified nominal models are used for designing controllers along with two different types of uncertainty models. Robustness refers to maintain- ing tracking performance under analytical model errors and dynamically induced eddy currents, while external disturbances are not considered. Results show that incorporating robustness into analytical models gives significantly better results. However, incorporating incorrect uncertainty models may lead to poorer performance than not designing for robustness at all. Designing controllers based on accurate identified models gave the best performance. In fact, incorporating a significant level of robustness into an accurate nominal model resulted in reduced performance. This paper discusses an assortment of experimental results in a consistent manner using robust control theory.
    Keywords: Mechanical Engineering
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  • 3
    Publication Date: 2019-07-10
    Description: The state-dependent Riccati equations (SDRE) is the basis of a technique for suboptimal feedback control of a nonlinear quadratic regulator (NQR) problem. It is an extension of the Riccati equation used for feedback control of linear problems, with the addition of nonlinearities in the state dynamics of the system resulting in a state-dependent gain matrix as the solution of the equation. In this paper several variations on the SDRE-based method will be considered for the feedback control problem with control nonlinearities. The control nonlinearities may result in complications in the numerical implementation of the control, which the different versions of the SDRE method must try to overcome. The control methods will be applied to three test problems and their resulting performance analyzed.
    Keywords: Numerical Analysis
    Type: NASA/CR-2004-213245 , NIA-2004-08
    Format: application/pdf
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