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Abstract
The present thesis is concerned with different aspects of modelling, control and identification of linear systems. Traditionally, discretetime sampleddata systems are represented using shiftoperator parametrizations. Such parametrizations are not suitable at fast sampling rates. An alternative parametrization using the socalled deltaoperator is examined. It is shown how to maintain a close correspondence to continuoustime when sampling a system described in continuoustime by stochastic differential equations. Using deltaoperator parametrizations makes it possible to unify discretetime and continuoustime theory. In addition these parametrizations possess certain numerical advantages compared to shiftoperator representations. A new prediction method is developed. It is based on ideas from continuoustime but derived from discretetime deltaoperator models. It is shown to include the optimal minimumvariance predictor as a special case and to have a welldefined continuoustime limit. By means of this new prediction method a unified framework for discretetime and continuoustime predictive control algorithms is developed. This contains a continuoustime like discretetime predictive controller which is insensitive to the choice of sampling period and has a welldefined limit in the continuoustime case. Also more conventional discretetime predictive control methods may be described within the unified approach. The predictive control algorithms are extended to frequency weighted criterion functions. Also a statespace approach is described which extends straightforwardly to the multivariable case. Finally, aspects on the connection between system identification and control design are discussed. Several approaches to improve this interconnection have been proposed. The frequencydistribution of the estimation error with lowcomplexity models is treated and proves to be important for the development of controlrelevant prefilters in estimation. Iterative approaches are presented, both using standard estimation methods with prefiltering and nonstandard controlrelevant estimation methods. New combined adaptive/iterative techniques are proposed.
Original language  English 

Place of Publication  Kgs. Lyngby 

Publisher  Technical University of Denmark 
Number of pages  292 
Publication status  Published  1997 
Series  IMMPHD199727 

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Dive into the research topics of 'DeltaDomain Predictive Control and Identification for Control'. Together they form a unique fingerprint.Projects
 1 Finished

Connection between control design and system identifikation
Lauritsen, M. B., Egardt, B. & Poulsen, N. K.
01/02/1994 → 24/07/1997
Project: PhD