000			01423 a2200241 4500
003			OSt
005			20230127170511.0
008			230127b xxu||||| |||| 00| 0 eng d
020			_a9780136251798
040			_cIIT Kanpur
041			_aeng
082			_a629.8 _bN731
245			_aNonlinear process control _cedited by Michael Henson A. and Dale E. Seborg
260			_bPrentice Hall _c1997 _aNew Jersey
300			_axii, 432p
520			_aChemical engineers assemble the theoretical and practical research on the design, analysis, and application of nonlinear process control strategies, much easier of late because of model- based approaches and more inexpensive and powerful computers. They outline the issues driving the research and several classic techniques, and provide a detailed introduction to nonlinear process modeling. Then they describe the two leading approaches of input/output linearization and nonlinear predictive control, show how to design state observers that permit control even if on-line measurements of all state variables cannot be obtained, and discuss new techniques for developing empirical models using artificial neural networks. Annotation c. by Book News, Inc., Portland, Or.
650			_aNonlinear control theory
650			_aAutomatic control
650			_aChemical process control
700			_aHenson, Michael A.[ed.]
700			_aSeborg, Dale E.[ed.]
942			_cBK
999			_c566366 _d566366