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Intelligent Observer and Control Design for Nonlinear by Dierk Schröder (auth.), Prof. Dr.-Ing. Dr.-Ing. h. c. Dierk

By Dierk Schröder (auth.), Prof. Dr.-Ing. Dr.-Ing. h. c. Dierk Schröder (eds.)

Control concept of nonlinear structures, within which both the linear half is understood however the proper nonlinearities in position, sort or parameters are unknown, or either the linear and the nonlinear components are in part or maybe so much unknown, is a brand new, difficult and hugely fascinating box. This ebook treats the matter by means of focussing at the function of studying. clever studying concepts may be able to make certain the unknown elements of nonlinear structures. those strategies are continuously strong and convergent. The equipment provided can be utilized either online and off-line. they've got functions in mechatronics, hydraulics and combustion engines.

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Additional resources for Intelligent Observer and Control Design for Nonlinear Systems

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Applied Nonlinear Control. Prentice-Hall International Editions, New Jersey, 1991. : A Direct Contral Method For a Class of Nonlinear Systems Using Neural Networks. 65, Cambridge University Engineering Department, Trumpington Street, Cambridge CB2 1PZ, March 1991. : Variable Structure System with Sliding Mode in Discontinuous Systems I, 11. Automation and Remote Control, 1972. : Sliding Modes in Contral and Optimization. Springer-Verlag, Berlin, Heidelberg, 1992. : Feedback Linearization Families for Nonlinear Systems.

2 we have seen that the system has an ideal behaviour when a stiff coupling is assumed between the masses. Now we include a gear box in our considerations, so we have to take into account that this can also lead to an ideal system behaviour if the gear box ratio is very high. 51 ) Gs(s) = (GM + G *) s L This also holds true for mechanical systems of higher order. The Lagrange approach of modeling the linear part of mechanical systems has the following advantages: 1. Due to the basic engineering knowledge of the real mechanical system a low order can be chosen for the model and most of the linear parameters can easily be determined.

Due to its high order, the model can no longer be used for the controller design. • Therefore, a reduction of the order of the linear system is necessary, for example by the method of Litz [8]. Nevertheless, severe problems will remain. • The interpretation of the reduced system in relation to the real physical system is not possible. 1 Control of Electromechanical Systems 41 difficult when unacceptable stresses of the mechanical components and instability should be avoided in the real system .

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