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Output-feedback Design for Non-smooth Mechanical Systems. Control Synthesis and Experiments

Автор:   Apostolos D.
мягкая обложка
212 страниц
2008 год
Издательство:   Книга по Требованию
3231 руб
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Описание:To show the strengths, weaknesses and potential of output-feedback controllers beyond their theoretical importance, it is indispensable to evaluate them in experimental setups. In the latter context, the focus is on the application area of mechanical systems with set-valued friction characteristics, where the friction is non-collocated with the control action. In this book, the focus is on two control problems for non-smooth systems. Firstly, the disturbance attenuation problem for piecewise linear (PWL) and piecewise affine (PWA) systems is studied. Here, we focus on applications in the field of perturbed flexible mechanical systems with PWL restoring characteristics. Secondly, the stabilization problem for Lur’e type systems with set-valued nonlinearities is examined. Therefore, the presented strategies are implemented to two case studies: i) a PWL system, ii) a dynamic rotor system with friction. These case studies can be considered as benchmarks for the proposed strategies for non- smooth and discontinuous systems. To deal with both the disturbance attenuation and the stabilization problem, observer- based output-feedback control strategies are proposed.

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Coders at Work: Reflections on the craft of programming

We donБЂ™t have this nightmare of installing updates. So it makes it easier for us to say, БЂњWeБЂ™re just going to launch things and get some feedback from the users and fix the stuff that needs to be fixed and donБЂ™t worry about the other stuff.БЂ« Seibel: If youБЂ™re working on the design of a big system what are the tools you useБЂ”do you sit down with a pad of graph paper or a UML drawing tool? Norvig: I never liked any of these UML-type tools. I always thought, БЂњIf you canБЂ™t do it in the language itself thatБЂ™s a weakness of the language.БЂ« I think a lot of what youБЂ™re doing, youБЂ™re dealing at a higher level. At Google a lot of what we do is figuring out how to break things up and parallelize them. WeБЂ™re going to necessarily run this on multiple machines but weБЂ™ve got so many users and, for many applications, so much data; howБЂ™s that going to work? So weБЂ™re thinking more at the level of machines and racks of machines rather than at the level of functions and interactions. Once you get that straightened out, then you can start diving into individual functions and methods ...»

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