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Titlebook: Digital Control Systems; Volume 2: Stochastic Rolf Isermann Textbook 1991Latest edition Springer-Verlag Berlin Heidelberg 1991 Markov.Regel

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書目名稱Digital Control Systems
副標(biāo)題Volume 2: Stochastic
編輯Rolf Isermann
視頻videohttp://file.papertrans.cn/280/279185/279185.mp4
圖書封面Titlebook: Digital Control Systems; Volume 2: Stochastic Rolf Isermann Textbook 1991Latest edition Springer-Verlag Berlin Heidelberg 1991 Markov.Regel
描述The great advances made in large-scale integration of semiconductors and the resulting cost-effective digital processors and data storage devices determine the present development of automation. The application of digital techniques to process automation started in about 1960, when the first process computer was installed. From about 1970 process computers with cathodic ray tube display have become standard equipment for larger automation systems. Until about 1980 the annual increase of process computers was about 20 to 30%. The cost of hardware has already then shown a tendency to decrease, whereas the relative cost of user software has tended to increase. Because of the high total cost the first phase of digital process automation is characterized by the centralization of many functions in a single (though sometimes in several) process computer. Application was mainly restricted to medium and large processes. Because of the far-reaching consequences of a breakdown in the central computer parallel standby computers or parallel back-up systems had to be provided. This meant a substantial increase in cost. The tendency to overload the capacity and software problems caused further di
出版日期Textbook 1991Latest edition
關(guān)鍵詞Markov; Regelungstheorie; algorithms; computer; control; control system; control theory; design; mechanical
版次2
doihttps://doi.org/10.1007/978-3-642-86420-9
isbn_softcover978-3-642-86422-3
isbn_ebook978-3-642-86420-9
copyrightSpringer-Verlag Berlin Heidelberg 1991
The information of publication is updating

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Structures of Multivariable Processesriable processes influence each other, resulting in mutual interactions of the direct signal paths .. — .... — .., etc. The internal structure of multivariable processes has a significant effect on the design of multivariable control systems. This structure can be obtained by theoretical modelling i
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Parameter-optimized Multivariable Control Systemsn criteria or tuning rules. Unlike single variable control systems, the structure of a multivariable controller consists not only of the order of the different control algorithms but also of the mutual arrangement of the coupling elements, as in chapter 18. Corresponding to the main and coupling tra
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