Directions in Mathematical Systems Theory and Optimization
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The work Directions in Mathematical Systems Theory and Optimization represents a distinct intellectual or artistic creation found in Boston University Libraries. This resource is a combination of several types including: Work, Language Material, Books.
The Resource
Directions in Mathematical Systems Theory and Optimization
Resource Information
The work Directions in Mathematical Systems Theory and Optimization represents a distinct intellectual or artistic creation found in Boston University Libraries. This resource is a combination of several types including: Work, Language Material, Books.
 Label
 Directions in Mathematical Systems Theory and Optimization
 Statement of responsibility
 edited by Anders Rantzer, Christopher I. Byrnes
 Subject

 Systems and Information Theory in Engineering
 Engineering
 Vibration, Dynamical Systems, Control
 Complexity
 Systems Theory, Control
 Vibration
 Vibration
 Electronic resources
 Vibration
 Engineering
 Control Engineering
 Numerical and Computational Methods in Engineering
 Engineering
 Physics
 Physics
 Systems theory
 Physics
 Language
 eng
 Summary
 For more than three decades, Anders Lindquist has delivered fundamental cont butions to the ?elds of systems, signals and control. Throughout this period, four themes can perhaps characterize his interests: Modeling, estimation and ?ltering, feedback and robust control. His contributions to modeling include seminal work on the role of splitting subspaces in stochastic realization theory, on the partial realization problem for both deterministic and stochastic systems, on the solution of the rational covariance extension problem and on system identi?cation. His contributions to ?ltering and estimation include the development of fast ?ltering algorithms, leading to a nonlinear dynamical system which computes spectral factors in its steady state, and which provide an alternate, linear in the dimension of the state space, to computing the Kalman gain from a matrix Riccati equation. His further research on the phase portrait of this dynamical system gave a better understanding of when the Kalman ?lter will converge, answering an open question raised by Kalman. While still a student he established the separation principle for stochastic function differential equations, including some fundamental work on optimal control for stochastic systems with time lags. He continued his interest in feedback control by deriving optimal and robust control feedback laws for suppressing the effects of harmonic disturbances. Moreover, his recent work on a complete parameterization of all rational solutions to the NevanlinnaPick problem is providing a new approach to robust control design
 Image bit depth
 0
 Literary form
 non fiction
 Series statement
 Lecture Notes in Control and Information Sciences,
 Series volume
 286
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