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contributor authorZeman, Paul
contributor authorKemmetmüller, Wolfgang
contributor authorKugi, Andreas
date accessioned2017-11-25T07:20:49Z
date available2017-11-25T07:20:49Z
date copyright2017/24/5
date issued2017
identifier issn0022-0434
identifier otherds_139_08_081008.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4236682
description abstractVariable displacement axial piston units are the core components of many hydrostatic and hydraulic hybrid drive trains. Therein, the fast and accurate control of the swash plate angle, utilizing the full possible dynamics of the displacement system, is essential for a good performance of the overall drive train. This paper describes the development, implementation, and the experimental validation of a control strategy for the swash plate angle based on nonlinear model predictive control (NMPC). A tailored mathematical model, which serves as the basis for the NMPC, is described in the first part of the paper. Two versions of NMPC, an indirect and a direct method, are compared with respect to their numerical complexity and their capability of handling input and state constraints. An observer strategy, which is designed to obtain the nonmeasurable states and varying parameters of the system, completes the overall control strategy. To reduce the negative influence of stick–slip friction, the concept of dithering is applied in the experimental implementation. The differences of the NMPC methods are analyzed by simulation studies and experiments. Finally, the experimental results, using an industrial electronic control unit (ECU), prove the practical feasibility and the improved control accuracy and robustness in comparison to classical (nonlinear) control strategies.
publisherThe American Society of Mechanical Engineers (ASME)
titleNonlinear Model Predictive Control of Axial Piston Pumps
typeJournal Paper
journal volume139
journal issue8
journal titleJournal of Dynamic Systems, Measurement, and Control
identifier doi10.1115/1.4035608
journal fristpage81008
journal lastpage081008-11
treeJournal of Dynamic Systems, Measurement, and Control:;2017:;volume( 139 ):;issue: 008
contenttypeFulltext


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