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Download Modeling, Control and Optimization of Complex Systems: In by Jian Song (auth.), Weibo Gong, Leyuan Shi (eds.) PDF

By Jian Song (auth.), Weibo Gong, Leyuan Shi (eds.)

Modeling, regulate And Optimization Of advanced Systems is a set of contributions from prime foreign researchers within the fields of dynamic structures, regulate idea, and modeling. those papers have been offered on the Symposium on Modeling and Optimization of complicated platforms in honor of Larry Yu-Chi Ho in June 2001. They comprise intriguing study subject matters corresponding to:

-modeling of advanced structures,
-power regulate in advert hoc instant networks,
-adaptive keep an eye on utilizing a number of types,
-constrained regulate,
-linear quadratic keep an eye on,
-discrete occasions,
-Markov determination methods and reinforcement studying,
-optimal keep an eye on for discrete occasion and hybrid platforms,
-optimal illustration and visualization of multivariate facts and capabilities in low-dimensional areas.

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P. Holl, W. Marquardt, and E. D. " Computers in Chemical Engineering, 14, pp. 1289-1295. [41] Larsson, M. " In Modelica 2000. Lund University, Lund, Sweden. [42] Lewis, R. (1998): Programming Industrial Control Systems Using IEC 1131-3. lEE, London. [43] Ljung, L. (1987): System Identification-Theory for the User. Prentice Hall, Englewood Cliffs, New Jersey. [44] Marquardt, W. " In Proc. Chemical Process Control IV. Cache, Elsevier, Amsterdam. [45] Mattsson, S. , M. Andersson, and K. J. , CAD for Control Systems, chapter 2, pp.

McGraw-Hill, New York, NY. , M. Blaha, W. Premerlani, F. Eddy, and W. L. (Contributor) (1991): Object-Oriented Modeling and Design. Prentice Hall, Englewood Cliffs, NJ. , A. " Technical Report. Department of Building Sciences, The Royal Institute of Technology, Stockholm, Sweden. [62] Sargent, R. W. H. and A. W. " Trans. Inst. Chern. Eng. (London), 42, pp. 190-197. [63] Shearer, J. L. and B. T. Kulakowski (1990): Dynamic Modeling and Control of Engineering Systems. Macmillan, New York, NY. ), J.

Model simplification is closely related to the descriptions of uncertainty. For the purposes of control it is essential to have some way to express the uncertainty of a model. There is clearly a trade off between model complexity and model uncertainty. Unfortunately there are no general methods for the key problems stated above for general systems. A user therefore has to resort to experimentation by making different simplifications and comparing the results. It is essential that a modeling environment can support such a procedure.

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