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Titlebook: Strategies for Feedback Linearisation; A Dynamic Neural Net Freddy Garces,Victor M. Becerra,Kevin Warwick Book 2003 Springer-Verlag London

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發(fā)表于 2025-3-21 19:54:59 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Strategies for Feedback Linearisation
副標(biāo)題A Dynamic Neural Net
編輯Freddy Garces,Victor M. Becerra,Kevin Warwick
視頻videohttp://file.papertrans.cn/879/878981/878981.mp4
概述COMPLEX NONLINEAR SYSTEMS ARE WIDESPREAD - THE READER WILL BE ABLE TO TREAT THEM AS SIMPLER LINEAR SYSTEMS..THESE ARE EASIER AND LESS EXPENSIVE TO DEAL WITH..THE READER WILL BE MADE AWARE OF THE MOST
叢書名稱Advances in Industrial Control
圖書封面Titlebook: Strategies for Feedback Linearisation; A Dynamic Neural Net Freddy Garces,Victor M. Becerra,Kevin Warwick Book 2003 Springer-Verlag London
描述The series Advances in Industrial Control aims to report and encourage of control technology transfer in control engineering. The rapid development technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Nonlinear control methods continue to exert a continuing fascination for current researchers in control systems techniques. Many industrial systems are nonlinear as was so ably demonstrated in the recent Advances in Industrial Control monograph on hydraulic servo-systems by M. Jelali and A. Kroll. However, the need to use a nonlinear control technique depends on the severity of the nonlinearity and the performance specification of the application. In some cases it is imperative that a nonlinear technique be used. The type
出版日期Book 2003
關(guān)鍵詞Extension; control; control theory; feedback; feedback control; identification; linearisation; mimo system;
版次1
doihttps://doi.org/10.1007/978-1-4471-0065-2
isbn_softcover978-1-4471-1095-8
isbn_ebook978-1-4471-0065-2Series ISSN 1430-9491 Series E-ISSN 2193-1577
issn_series 1430-9491
copyrightSpringer-Verlag London 2003
The information of publication is updating

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Case Studies,e approximate feedback linearisation of a simulated single link manipulator. Finally, Section 7.3 presents a case study involving identification and approximate feedback linearisation and decoupling of a simulated evaporator process.
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Feedback Linearisation Using Dynamic Neural Networks,duced practice and has the potential to increase the number of applications, as neural network models can be calculated from measured data from the plant, so avoiding the need for deriving a physical model of a possibly complex process.
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Book 2003chnology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers a
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Introduction,ping system’s variables at desired constant values, while tracking involves forcing them to follow prescribed trajectories. The control problem involves determining the values of the manipulated input using all available information to achieve the control objective.
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