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Analysis and Control of Nonlinear Process Systems by Katalin M. Hangos, József Bokor, Gábor Szederkényi

By Katalin M. Hangos, József Bokor, Gábor Szederkényi

Just about all procedure platforms are nonlinear in nature. Nonlinear keep watch over is commonly a space of curiosity in strategy structures engineering that's of serious useful value. those proof though, many approach engineers have hassle with the paradigms and result of glossy nonlinear regulate thought simply because they lack the mathematical history often linked to such equipment or as a result of the their computational trouble and small-scale applicability within the normal case. research and keep watch over of Nonlinear method platforms overcomes those boundaries. beneficial properties: · the mandatory mathematical preliminaries for readers from a procedure engineering historical past. · consistent connection with the widely-known finite-dimensional linear time-invariant non-stop case as a foundation for extension to the nonlinear scenario. · the main promising theories and analytical equipment for nonlinear technique keep an eye on laid out sincerely and straightforwardly with workouts to reaffirm the strategies as they're taught. · Emphasis at the significance of technique wisdom and first-principles-based versions in acquiring possible and potent options specifically conditions from basic circumstances. · representation of functions with easy examples and case stories. research and regulate of Nonlinear procedure platforms will curiosity graduate strategy engineers wishing to check complex keep an eye on equipment both to be able to extra learn or program in in addition to to lecturers looking to circulation approach keep an eye on classes into extra advanced yet updated territory. it's going to even be a superb information to these of their senior undergraduate years who will shape the subsequent new release of commercial technique engineers and want unfussy entry to the main glossy nonlinear regulate rules.

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Statespace models 4. Dynamic process models MODELING 5. Input— output models ANALYSIS 6. Controllability and observability 7. Stability, Lyapunov method 8. Passivity, Hamiltonian view CONTROL 9. State feedback controllers 10. Feedback and input output linearization 11. Passivation by feedback 12. 1. The road map of the book The first draft version of this material was used for an intensive four-week postgraduate course taught for process engineers in the CAPEC Center, De- 6 1. Introduction partment of Chemical Engineering, Technical University of Denmark (Lyngby, Denmark) in 2000.

An .. 0   .. .   .. .   .. . 1 0 with the coefficients of the polynomial a(s) = sn + a1 sn−1 + ...  0 C c = b 1 b2 . . b n with the coefficients of the polynomial b(s) = b1 sn−1 + ... 2). 3 Linear Time-varying (LTV) Parameter Systems The simplest extension to the basic LTI case is the case of linear time-varying parameter systems (abbreviated as LTV systems) in which we allow the parameters of an LTI system to be time-varying instead of being constant. In this way we can describe certain disturbances acting as parameters in the linear model if there is information on their time variation.

14) i=1 This way, we construct the parameter θ as a convex linear combination of the vectors {ω1 , ω2 , . . , ω }. This implies that every entry in the parameter vector is bounded. Again, special nonlinear systems, such as bilinear systems, can be described as affine LPV systems by considering some of the state and/or input signals as time-varying parameters. 1 by assuming that the model parameter U , the heat transfer coefficient, varies with time. 16) assuming all the remaining parameters vc , Vc , A, cP c , ρc , vh , Vh , cP h , ρh to be constants.

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