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Titlebook: Deterministic and Stochastic Time-Delay Systems; El-Kébir Boukas,Zi-Kuan Liu Book 2002 Springer Science+Business Media New York 2002 Marko

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發(fā)表于 2025-3-21 18:09:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Deterministic and Stochastic Time-Delay Systems
編輯El-Kébir Boukas,Zi-Kuan Liu
視頻videohttp://file.papertrans.cn/270/269351/269351.mp4
叢書名稱Control Engineering
圖書封面Titlebook: Deterministic and Stochastic Time-Delay Systems;  El-Kébir Boukas,Zi-Kuan Liu Book 2002 Springer Science+Business Media New York 2002 Marko
描述Most practical processes such as chemical reactor, industrial furnace, heat exchanger, etc., are nonlinear stochastic systems, which makes their con- trol in general a hard problem. Currently, there is no successful design method for this class of systems in the literature. One common alterna- tive consists of linearizing the nonlinear dynamical stochastic system in the neighborhood of an operating point and then using the techniques for linear systems to design the controller. The resulting model is in general an approximation of the real behavior of a dynamical system. The inclusion of the uncertainties in the model is therefore necessary and will certainly improve the performance of the dynamical system we want to control. The control of uncertain systems has attracted a lot of researchers from the control community. This topic has in fact dominated the research effort of the control community during the last two decades, and many contributions have been reported in the literature. Some practical dynamical systems have time delay in their dynamics, which makes their control a complicated task even in the deterministic case. Recently, the class ofuncertain dynamical deterministic
出版日期Book 2002
關(guān)鍵詞Markov; Markov process; algorithm; control engineering; dynamical systems; filtering problem; stochastics
版次1
doihttps://doi.org/10.1007/978-1-4612-0077-2
isbn_softcover978-1-4612-6602-0
isbn_ebook978-1-4612-0077-2Series ISSN 2373-7719 Series E-ISSN 2373-7727
issn_series 2373-7719
copyrightSpringer Science+Business Media New York 2002
The information of publication is updating

書目名稱Deterministic and Stochastic Time-Delay Systems影響因子(影響力)




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書目名稱Deterministic and Stochastic Time-Delay Systems網(wǎng)絡(luò)公開度學(xué)科排名




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Robust Stability and Robust Stabilizability,ractical systems with a linear model having some uncertainties. The presence of these uncertainties in the dynamics requires the establishment of robust conditions that can guarantee the stability and/or the stabilizability of the practical system under study. This topic has in fact dominated the re
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Control and Filtering,idered during the design phase. In the current literature there are many ways to eliminate the effects of the external disturbances. One of them is the -1.control technique. It consists of designing a suboptimal control that minimizes the effects of the external disturbance on the output. In other w
5#
發(fā)表于 2025-3-22 09:50:11 | 只看該作者
,Robust ‘H∞Control, Filtering, and Guaranteed Cost Control, Since these algorithms are based on nominal systems, there is no guarantee that the robustness of system performance will be assured in the presence of uncertainties. To overcome this and avoid any trouble we may have, we should take into account system uncertainties during the analysis and the des
6#
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Stability and Stabilizability of Markov Jump Systems,ider a hybrid system with.modes, that is.{1, 2, ? ? ?, N}. Mode switching is assumed to be governed by a continuous-time Markov process {r.t > Of taking values in the state space.and having the following infinitesimal generator
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Control and Filtering Problems for Markov Jump Systems with Time Delay,y inefficient for eliminating the effect of the disturbance. One alternative is to use the R.control, which entails searching for a controller that stabilizes the system, and at the same time assures disturbance rejection at a given level. The..control problem has received considerable attention and
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Robust , and Guaranteed Cost Control for Jump Linear Systems with Time Delay,n the neighborhood of the operating point. For many reasons well known in the control community, the systems parameters and the operating point change with time and therefore, the fixed linear Markov jump model is not adequate to guarantee robustness of system performance. Besides this, the system c
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