[Back]

M. Kozek:
"Modeling for Control Design -- Challenges and Pitfalls in a Demanding Task";
Keynote Lecture: CSSim2011, 2nd International Conference on Computer Modelling and Simulation, Brno, Czech Republic (invited); 2011-09-05 - 2011-09-07; in: "Proceedings of the 2nd International Conference on Computer Modelling and Simulation-CSSim2011", (2011), ISBN: 9788021443204; 47 pages.

Modeling for the design of a suitable control strategy is a multi-dimensional task. It requires the ability to trade between the demands of a design model with predefined structure and preferably low order and sufficient accuracy. The prediction fidelity of the design model itself is usually less important than the closed-loop performance of the resulting control scheme. The goals of the control application specify suitable control design methods, and the selected design method in turn requires a specific model structure. This specific model structure poses a strong constraint for the design task. Moreover, an additional high-fidelity simulation model is necessary to evaluate and assess the closed-loop performance prior to implementation. Quite often a more simple design model and a more complex validation model are developed either in series or in parallel to provide the necessary validation tools.
In this presentation different modeling approaches suitable for control design are presented and discussed. Identification procedures for linear as well as nonlinear black-box models are presented, analytical modeling of distributed and concentrated parameter systems is reviewed, and the advantages of a combined approach (grey models) are pointed out. The process of problem definition, control methodology selection, model design, validation, and implementation is laid out and problems of each stage are addressed. Implementation examples are given for different industrial applications, including co-simulation studies and large-scale industrial implementations.