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Titlebook: Development of control concepts for improved driving dynamics of harvesting machines with large head; Benedikt Jung Book 2019 Springer-Ver

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樓主: Fixate
11#
發(fā)表于 2025-3-23 12:53:53 | 只看該作者
Key conclusion and future work,This chapter summarizes the content of each chapter briefly, presents key conclusions and suggests future work.
12#
發(fā)表于 2025-3-23 16:34:43 | 只看該作者
Book 2019thor explores a common problem that hinders machine performance when harvesting with very large headers. He deals with concepts for reducing the undesired effects of vehicle dynamics when using these machines.??.With the steadily increasing capacity of harvesting machines, the working widths of the
13#
發(fā)表于 2025-3-23 21:28:26 | 只看該作者
14#
發(fā)表于 2025-3-23 22:21:12 | 只看該作者
15#
發(fā)表于 2025-3-24 02:44:19 | 只看該作者
2524-3365 dynamic wheel loads.Contains results from simulations and m.This book examines the driving dynamics of harvesting machines with large harvesting heads. It looks at how to efficiently use these machines. The author explores a common problem that hinders machine performance when harvesting with very
16#
發(fā)表于 2025-3-24 06:43:41 | 只看該作者
17#
發(fā)表于 2025-3-24 13:07:48 | 只看該作者
18#
發(fā)表于 2025-3-24 18:19:30 | 只看該作者
https://doi.org/10.1007/978-3-642-47394-4mping ratios of the harvesting machine are derived, and a sensitivity analysis is performed. The chapter ends with a discussion of potential solution approaches to the header height control problem under investigation
19#
發(fā)表于 2025-3-24 21:33:23 | 只看該作者
Vehicle dynamics modelling and model analysis,mping ratios of the harvesting machine are derived, and a sensitivity analysis is performed. The chapter ends with a discussion of potential solution approaches to the header height control problem under investigation
20#
發(fā)表于 2025-3-25 00:13:21 | 只看該作者
https://doi.org/10.1007/978-3-322-80804-2f a combine harvester, the signal pre-processing and the determination of the order of the estimator model. In addition, it is explained how the natural frequency and damping ratio is derived from the coefficients of the estimator model. The chapter ends with a step-wise validation of the adaptive command shaping concept with real machine data.
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