Bounding Approaches to System Identification
M. Milanese, J. Norton, E. Walter, H. Piet-Lahanier, É. Walter
Springer US, May 31, 1996 - Language Arts & Disciplines - 565 pages
In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.
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Overview of the Volume I
Solving Linear Problems in the Presence of Bounded Data
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adaptive algorithm applications approach approximation associated assumed assumptions Automatica belong bounds chapter complexity computed considered consists constraints containing Control convergence convex corresponding criterion defined denoted depends described determined disturbance dynamic elements ellipsoid equation error evaluation exact example feasible FIGURE function given gives hyperplanes identification IEEE Trans inequalities initial input interest intersection interval Italy known linear matrix means measurement method Milanese minimal noise Note obtained optimal outer outliers output parameter Parameter Estimation performance polytope possible prediction presented Press priori problem procedure Proceedings projection provides recursive represented respectively robust samples satisfies sequence shown shows signal Simul solution solving space Step Table techniques Theorem true uncertainty unknown update upper values variables vector vertices volume Walter weights York