Analysis and Control of Nonlinear Process Systems by Katalin M. Hangos, Jozsef Bokor, Gabor Szederkenyi PDF

By Katalin M. Hangos, Jozsef Bokor, Gabor Szederkenyi

ISBN-10: 1852336005

ISBN-13: 9781852336004

This simple textual content makes the complex yet strong tools of non-linear keep an eye on obtainable to strategy engineers. not just does it disguise the mandatory arithmetic, however it continually refers back to the widely-known finite-dimensional linear time-invariant non-stop case as a foundation for extension to the nonlinear situation.

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Calculate g(t) t ≥ 0 and g ∞ . 7. 6 and check the convolution theorem for the Laplace transform of f1 and f2 . TLFeBook This page intentionally left blank TLFeBook 3. State-space Models State-space models are the natural form of system models for a process engineer. The reason for this is that process engineering models originating from first engineering principles can be transformed into state-space form in the majority of practically important cases [32]. As a consequence, state variables in a process system model possess a clear engineering meaning – they are the canonical set of conserved extensive quantities in the process system.

Linear time-invariant state-space models A classical well-known state-space model class for which closed analytical solutions exist for most of the analysis and control problems [9], [39]. • Linear time-varying and linear parameter-varying systems Special system classes which are relatively easy-to-handle extensions of the classical LTI case but are capable of describing some of the essentially nonlinear system classes. • Nonlinear concentrated parameter state-space models The input-affine form [37] is the system class this book deals with.

2. e. they have continuous partial derivatives of any order. A transformation of this type is called a global diffeomorphism on Rn . 1 (A simple nonlinear state transformation) Consider a simple nonlinear vector-vector function f f (x1 , x2 ) = f (x) = x21 + x22 x31 + x32 and let the function Φ generating the coordinate transformation be given as √ x z = Φ(x) = √ 1 x2 which is invertible on the domain x1 ≥ 0, x2 ≥ 0. Its inverse function is: z2 x = Φ−1 (z) = 12 z2 Therefore the original function f in the transformed coordinate system will be: f (z) = f (Φ−1 (z)) = z14 + z24 z16 + z26 Sometimes, a transformation having both of these properties and being defined for all x is difficult to find.

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Analysis and Control of Nonlinear Process Systems by Katalin M. Hangos, Jozsef Bokor, Gabor Szederkenyi


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