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Abstract

The field of stochastic state-multiplicative control and filtering has greatly matured since, its emergence in the 60’s of the last century [72], [91], [92], [93], [97], [100], [102], [121], [122], [124], [125], (see also [16], [53], [80] for extensive review). The linear quadratic optimization problems (stochastic H 2) that were treated in the first two decades cleared the way, in the mid 80s, to the H  ∞  worst case control strategy, resulting in a great expansion of research effort, aimed at the solution of related problems such as state-feedback control, estimation, dynamic output-feedback control, preview tracking control and zero-order control among other problems, for various types of nominal and uncertain systems [13], [24]-[28], [44]-[54], [94], [95], [99], [115] (see also [53] for extensive review).

Keywords

Linear Matrix Inequality Stochastic System Wiener Process Borel Measurable Function Nonlinear Stochastic System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.Department of Electrical and Electronics EngineeringHolon Institute of TechnologyHolonIsrael
  2. 2.School of Electrical EngineeringTel Aviv UniversityRamat AvivIsrael

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