Displaying similar documents to “The selection of input and output schemes for a system and the model projection problems”

Continuous-time input-output decoupling for sampled-data systems

Osvaldo Maria Grasselli, Laura Menini (1999)

Kybernetika

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The problem of obtaining a continuous-time (i. e., ripple-free) input-output decoupled control system for a continuous-time linear time-invariant plant, by means of a purely discrete-time compensator, is stated and solved in the case of a unity feedback control system. Such a control system is hybrid, since the plant is continuous-time and the compensator is discrete-time. A necessary and sufficient condition for the existence of a solution of such a problem is given, which reduces the...

Derivation of effective transfer function models by input, output variables selection

Nicos Karcanias, Konstantinos G. Vafiadis (2002)

Kybernetika

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Transfer function models used for early stages of design are large dimension models containing all possible physical inputs, outputs. Such models may be badly conditioned and possibly degenerate. The problem considered here is the selection of maximal cardinality subsets of the physical input, output sets, such as the resulting model is nondegenerate and satisfies additional properties such as controllability and observability and avoids the existence of high order infinite zeros. This...

Extension of first order Predictive Functional Controllers to handle higher order internal models

Mohamed Tarek Khadir, John V. Ringwood (2008)

International Journal of Applied Mathematics and Computer Science

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Predictive Functional Control (PFC), belonging to the family of predictive control techniques, has been demonstrated as a powerful algorithm for controlling process plants. The input/output PFC formulation has been a particularly attractive paradigm for industrial processes, with a combination of simplicity and effectiveness. Though its use of a lag plus delay ARX/ARMAX model is justified in many applications, there exists a range of process types which may present difficulties, leading...

System identification from multiple-trial data corrupted by non-repeating periodic disturbances

Minh Phan, Richard Longman, Soo Lee, Jae-Won Lee (2003)

International Journal of Applied Mathematics and Computer Science

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Iterative learning and repetitive control aim to eliminate the effect of unwanted disturbances over repeated trials or cycles. The disturbance-free system model, if known, can be used in a model-based iterative learning or repetitive control system to eliminate the unwanted disturbances. In the case of periodic disturbances, although the unknown disturbance frequencies may be the same from trial to trial, the disturbance amplitudes, phases, and biases do not necessarily repeat. Furthermore,...