By Katalin M. Hangos, Jozsef Bokor, Gabor Szederkenyi
This easy textual content makes the advanced yet robust equipment of non-linear keep an eye on available to method engineers. not just does it conceal the mandatory arithmetic, however it continuously 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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Extra resources for Analysis and Control of Nonlinear Process Systems
For this, consider a finite dimensional normed linear space ν equipped with a norm · ν . TLFeBook 16 2. 9 (Lq spaces, vector case) For q = 1, 2, . . 10 (q-norm, vector case) Let f ∈ Lq (ν) for q = 1, 2, . . 11 (Lqe spaces, vector case) For q = 1, 2, . . the signal space Lqe (ν) consists of the functions f : R+ 0 → ν, which are Lebesgue-measurable and fT ∈ Lq (ν) for all T, 0 ≤ T < ∞. Special Cases. 2). 1. 26) 0 2. 4 (Signal spaces and their relations) Besides the Lq -spaces, we can define many other signal spaces.
The independent variables in this case are the screen coordinates (x and y) and time (t). 2 Classification of Signals Signals are classified according to the properties of their independent and dependent variables. Dimensionality of the Independent Variable. The independent variable can have one or more dimensions. The most common one-dimensional case is when the independent variable is time. Dimension of the Dependent Variable (Signal). The signal value evaluated at a certain point in its domain can also be one or more dimensional.
Chapter 8 is devoted to passivity analysis and the Hamiltonian description, which are powerful concepts with an important physical basis in the case of process systems, • Nonlinear feedback control (Chapters 9–12). An introductory chapter (Chapter 9) deals with the basic notions and techniques for state feedback control, in particular pole-placement and LQR control of linear time-invariant systems. Thereafter separate chapters deal with the most important special techniques for nonlinear process control: feedback and input–output linearization, passivation and stabilization and loop-shaping based on the Hamiltonian view.
Analysis and Control of Nonlinear Process Systems by Katalin M. Hangos, Jozsef Bokor, Gabor Szederkenyi