Abstract
Parameter estimation and optimal design of experiments are important steps in establishing models that reproduce a given process quantitatively correctly. The methods for parameter estimation and optimum experimental design are being more and more often applied in industry. The realization of methods in industrial practice shows however, that in order to use the complete potential of nonlinear optimum experimental design, we have to deal with several mathematical challenges. This article presents very effective algorithms for design of optimal experiments in dynamic systems and preliminary numerical results for dynamic robot calibration.
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